District heating system's development decarbonization strategy assessment by system dynamics modeling and multi-criteria analysis.

The study introduces a hybrid model that integrates system dynamics modeling and multi-criteria analysis. Through the system dynamics model, the study examines energy, economic, and environmental indicators of a District Heating (DH) company, assessing its dynamics until 2050. Various decarbonization scenarios are explored, involving the transition of the DH system to a 4th generation DH (4GDH) system based on four strategies: utilizing at least (a) 50% Renewable Energy Sources (RES), (b) 50% waste heat, (c) 75% cogenerated heat, or (d) 50% of the combined aforementioned energy and heat. Additionally, development scenarios incorporate measures to enhance energy efficiency on the consumer side and within the heating networks. The sustainability of each scenario is evaluated using the multi-criteria analysis method TOPSIS. The hybrid model establishes a ranking of the transition pathways based on their sustainability scores and benchmarks the results of the developed scenarios against a carbon-neutral DH system. This model serves as a valuable guide for DH system developers and decision-makers. The study focuses on Riga as a practical case study.

Using Analytic Hierarchy Process to Assess Beekeeping Suitability in Portuguese Controlled Areas: A First Approach.

Beekeeping management is greatly influenced by spatial factors (e.g., land use/land cover, roads, or electrical energy networks), so GIS are a powerful tool to overlap and relate a variety of spatial data levels and, consequently, a very useful tool for beekeeping activity planning. This study was developed within the intervention area of three controlled zones managed by Portuguese Beekeepers Associations. The methodology, based on multi-criteria decision analysis, integrates several criteria, such as hydrographic networks, road networks, soil occupation, solar radiation, and electromagnetic radiation sources. These criteria were proposed and evaluated through online questionnaires carried out with beekeepers. Concerning the selected criteria and the respective geographical data, the most relevant were land use/land cover and water availability, with a significance of 44% and 24%, respectively. The beekeeping suitability map enabled us to evaluate the degree of compliance for the actual location of apiaries, with 60% of the apiaries being installed in high potential areas. In the context of beekeeping planning, the potential of the techniques applied seems to be an important tool for optimizing the location of apiaries and the profitability of beekeeping.

Natural gas based on combined fuzzy TOPSIS technique and entropy.

In the present study we have presented the notion of FUZZY BAYESIAN DECISION TECHNIQUE and combined the idea of the Fuzzy TOPSIS technique and entropy. We define the new ideas of fuzzy TOPSIS technique and entropy. So, we introduce the TOPSIS method and entropy, and the weights of the DMs are used. We proposed an MCDM technique based on TOPSIS and entropy. We focus on parameter different solutions of Fuzzy TOPSIS Positive ideal and Negative ideal solutions efficient decision making. Also, we provide a numerical example to elucidate the proposed technique stage by stage. Lastly, we compare the explanations of the current problem with the many existing MCGDM approaches to deliver the skills and rationality of the offered technique. We also provide a sensitivity study by shifting the entropy to establish the weights of the criteria underneath the dominant entropy measure meaning.

Mapping soil suitability using phenological information derived from MODIS time series data in a semi-arid region: A case study of Khouribga, Morocco.

To address the increasing global demand for food, it is crucial to implement sustainable agricultural practices, which include effective soil management techniques for enhancing productivity and environmental conditions. In this regard, a study was conducted to assess the efficacy of utilizing phenological metrics derived from satellite data in order to map and identify suitable agricultural soil within a semi-arid region. Two distinct methodologies were compared: one based on physicochemical soil parameters and the other utilizing the phenological response of vegetation through the application of the Normalized Difference Vegetation Index (NDVI) Modis-time series. The study findings indicated that the NDVI-based approach successfully identified a specific class of soil suitability for agriculture (referred to as S1) that could not be effectively mapped using the multi-criteria analysis (MCAD) method relying on soil physicochemical parameters. This S1 class of soil suitability accounted for approximately 5 % of the total study area. These outcomes suggest that phenological-based approaches offer greater potential for spatio-temporal monitoring of soil suitability status compared to MCAD, which heavily relies on discrete observations and necessitates frequent updates of soil parameters. The approach developed to map the soil-suitability is a valuable tool for sustainable agricultural development, and it can play an effective role in ensuring food security and conducting a land agriculture assessment.

Assessment of UTI Diagnostic Techniques Using the Fuzzy-PROMETHEE Model.

Accurate diagnosis of urinary tract infections (UTIs) is important as early diagnosis increases treatment rates, reduces the risk of infection and disease spread, and prevents deaths. This study aims to evaluate various parameters of existing and developing techniques for the diagnosis of UTIs, the majority of which are approved by the FDA, and rank them according to their performance levels. The study includes 16 UTI tests, and the fuzzy preference ranking organization method was used to analyze the parameters such as analytical efficiency, result time, specificity, sensitivity, positive predictive value, and negative predictive value. Our findings show that the biosensor test was the most indicative of expected test performance for UTIs, with a net flow of 0.0063. This was followed by real-time microscopy systems, catalase, and combined LE and nitrite, which were ranked second, third, and fourth with net flows of 0.003, 0.0026, and 0.0025, respectively. Sequence-based diagnostics was the least favourable alternative with a net flow of -0.0048. The F-PROMETHEE method can aid decision makers in making decisions on the most suitable UTI tests to support the outcomes of each country or patient based on specific conditions and priorities.

Site suitability analysis for locating construction and demolition waste transfer station: an Indian case study.

Construction and Demolition Waste Management (CDWM) includes collecting, transporting, processing, and disposing construction and demolition (C&D) waste, where collection and transportation of bulky and voluminous C&D waste contribute significantly to economic and environmental impacts. Transfer station (TS) being a link between various waste management (WM) facilities plays a significant role in collection and transportation of waste. Thus, locating TS at suitable site can help in reducing the overall impacts. Employment of Geographic Information System (GIS) analysis tools in CDWM is a powerful strategy for site suitability study. A case study in Coimbatore, India, is presented in this study using GIS-based multi-criteria analysis for locating C&D waste TS. The criteria for site suitability analysis are chosen based on literature review, regulations, and experts' opinions. Weights of the chosen criteria are estimated using analytic hierarchy process (AHP), and the final suitability map is created by weighted overlay analysis (WOA) in GIS environment. Results provide first-hand information for local decision makers to locate C&D waste transfer station in the chosen study region and report that 12% of the entire area is "highly suitable" for transfer station location.

Geo-hazards assessment and land suitability estimation for spatial planning using multi-criteria analysis.

The fundamentals contribution of multi-hazard assessment lies in its ability to guide and identify directions for territorial development, aiming to reduce vulnerability through the implementation of appropriate measures. In the present study, Multi-Criteria Decision Making supported by Geographic Information System was utilized to solve spatial problems related to territorial sprawl. Considering this perspective, an analysis was conducted on the susceptibility of land to the occurrence of geo hazards in the Moldova catchment, situated in the northeastern region of Romania, within a transitional zone between mountains and plateaus. The analysis focused on assessing the likelihood of geo-hazards like floods, landslides, and earthquakes, utilizing the weights obtained through the implementation of the Analytical Hierarchy Process (AHP). Subsequently, the obtained results were utilized to generate a multi-hazard map, which facilitated the identification of areas that are suitable for territorial development. The results were validated in two ways: by sensitivity analysis in which two minimum and maximum scenarios were proposed concerning the result obtained and by validation using the receiver operating characteristic (ROC) curve method. The areas with high susceptibility to geo-hazards triggers are located in the southeastern part of the region, in the proximity of the hydrographic network. Flood risk is the hazard with the highest recurrence. Localities with high suitability for spatial development have a central-western distribution. According to the applied model, sites for each locality included in the study area can be identified. The high and very high suitability classes account for 54% of the total area, while the unsuitable classes represent 15% of the area. However, the vulnerability of the area and the need for the study are generated by 35% of the settlements being located in areas with high susceptibility.

Multi-Criteria Analysis of Startup Investment Alternatives Using the Hierarchy Method.

In this paper, we discuss the use of multi-criteria analysis for investment alternatives as a rational, transparent, and systematic approach that reveals the decision-making process during a study of influences and relationships in complex organizational systems. It is shown that this approach considers not only quantitative but also qualitative influences, statistical and individual properties of the object, and expert objective evaluation. We define the criteria for evaluating startup investment prerogatives, which are organized in thematic clusters (types of potential). To compare the investment alternatives, Saaty's hierarchy method is used. As an example, the analysis of three startups is carried out based on the phase mechanism and Saaty's analytic hierarchy process to identify investment appeal of startups according to their specific features. As a result, it is possible to diversify the risks of an investor through the allocation of resources between several projects, in accordance with the received vector of global priorities.

Smallholder oil palm plantation sustainability assessment using multi-criteria analysis and unmanned aerial vehicles.

Oil palm agriculture has caused extensive land cover and land use changes that have adversely affected tropical landscapes and ecosystems. However, monitoring and assessment of oil palm plantation areas to support sustainable management is costly and labour-intensive. This study used an unmanned aerial vehicles (UAV) to map smallholder farms and applied multi-criteria analysis to data generated from orthomosaics, to provide a set of sustainability indicators for the farms. Images were acquired from a UAV, with structure from motion (SfM) photogrammetry then used to produce orthomosaics and digital elevation models of the farm areas. Some of the inherent problems using high spatial resolution imagery for land cover classification were overcome by using texture analysis and geographic object-based image analysis (OBIA). Six spatially explicit environmental metrics were developed using multi-criteria analysis and used to generate sustainability indicator layers from the UAV data. The SfM and OBIA approach provided an accurate, high-resolution (~5 cm) image-based reconstruction of smallholder farm landscapes, with an overall classification accuracy of 89%. The multi-criteria analysis highlighted areas with lower sustainability values, which should be considered targets for adoption of sustainable management practices. The results of this work suggest that UAVs are a cost-effective tool for sustainability assessments of oil palm plantations, but there remains the need to plan surveys and image processing workflows carefully. Future work can build on our proposed approach, including the use of additional and/or alternative indicators developed through consultation with the oil palm industry stakeholders, to support certification schemes such as the Roundtable on Sustainable Palm Oil (RSPO).

Differences in perception of safety in driving environment according to shared PMD user experience through multi-criteria analysis.

A shared personal mobility device (PMD) is a transportation model that rents personal transportation devices, such as bicycles and kickboards, through a sharing platform. The use of shared PMD has increased, but related complaints and traffic accidents are doubling with it every year. This study applied an analytic network process (ANP) methodology for the multi-criteria analysis. A survey including normal citizens was conducted to evaluate the importance of safety regarding shared PMD experience. The evaluation factors differ according to the experience of using the shared PMD device, although 'driving continuity' and 'separation of sidewalks and roadways' were the most important. PMD users gave greater priority to 'removal of the road gap', 'traffic safety signs', 'dedicated parking area' and 'management of obstacles' compared to non-users. On the other hand, for non-PMD users, 'bicycle lane width', 'strengthening enforcement', and 'user safety education' were more important. The results showed that importance differed depending on the participant's experience of using a shared PMD or the lack of it. In the case of users, factors that have a direct effect on driving were prioritised, and in the case of non-users, auxiliary operations and management, such as crackdowns and education, were prioritised.

The Progress of the Development of a Climate-smart Agriculture in Europe: Is there Cohesion in the European Union?

The development of climate-smart agriculture (CSA) is crucial in ensuring the creation of a low-carbon society and mitigation of climate change. These tasks require concerted actions from multiple stakeholders since the very concept of CSA is rather complex and requires multi-dimensional consideration. This study defines and applies various indicators to evaluate the development of CSA in the European Union (EU). To do this, three different multi-criteria decision-making methods, namely Simple Additive Weighting (SAW), Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR; multi-criteria optimization and compromise solution), were employed for the construction of a composite indicator. A combination of both objective (entropy) and subjective (Analytic Hierarchy Process) weighting techniques was utilized to derive the weights of the indicators. The leaders in the EU in terms of CSA are Austria, Denmark and the Netherlands, whereas the countries with the lowest levels of CSA development are Cyprus, Greece and Portugal. This study also revealed divergence in the development of these practices in the EU-24 for the period 2004-2019. Thus, a more inclusive approach is needed to ensure the spread of climate-smart ideas in European agriculture sectors.

A multi-criteria analysis framework for water transfers to improve the water environments under strong artificial interventions in highly urbanized areas.

Water transfer is an effective measure to enhance hydrodynamic and water quality in highly urbanized areas. The effect of water transfer in highly urbanized areas is affected by strong artificial interventions, and it is difficult to evaluate the improvement of multiple indicators of many sections after water transfer. At present, there is no analysis framework directly evaluates the improvement of water environment under strong artificial interventions, making it difficult to determine the optimal scheduling of hydraulic projects. This study constructed a multi-criteria analysis framework for evaluating the improvement of water environment including index layers of water quality improvement, hydrodynamic improvement and economic cost, and designed corresponding element layers for each index layer. The weights of each element were determined based on fuzzy analytical hierarchy process, and the fuzzy comprehensive evaluation method was used for comprehensive evaluation. The framework was applied in Xishan District in highly urbanized Taihu Lake Basin, and the results showed that the proposed framework could effectively determine the optimal scheduling of hydraulic projects. Water quality compliance rate for the optimal water transfer scheme achieved in Xishan District was 82%, average rate of water quality improvement was 31%, and proportion of cross-sections meeting the Class III water quality standard was 61%. Average flow velocity was 0.10 m/s, proportion of the optimal velocity was 39%, and proportion of stagnant sections was 32%. Furthermore, the impact of regional control projects on the effect of water transfer was much greater than local projects, consequently, the best scheduling mode for regional control projects should be first determined, and then the scheduling combination for local projects. This study can provide a new framework for the assessment of water transfers to improve the water environments and a scientific basis for the dispatching of hydraulic projects in Taihu Lake Basin.

Reduction of pathogens in greywater with biological and sustainable treatments selected through a multicriteria approach.

Non-potable reuse of greywater (GW) can represent a valid alternative to freshwater consumption, satisfying the Sustainable Development Goals promoted by United Nations. The Multi-Criteria Analysis (MCA) was applied to select the most suitable processes for the reduction of microbiological contamination in GW. A pilot plant, including horizontal flow constructed wetland (CW) and anaerobic filtration (AF) in parallel, best treatment options according to MCA results, was built to treat GW collected from a Venezuelan family. (i) The removal efficiency of microbiological parameters, and (ii) the turbidity as possible microbiological contamination indicator and possible influence factor of disinfection treatment, were investigated. Except for Escherichia coli (4.1 ± 0.9 log reduction with AF), CW achieved the best reductions yields for total coliforms, faecal coliforms, and Salmonella, respectively equal to 3.1 ± 0.5 log, 4.3 ± 0.5 log, and 2.9 ± 0.4 log. In accordance with Venezuelan legislation and WHO guidelines, GW treated with CW was found to be suitable for irrigation reuse for non-edible crops. However, the reduction of pathogens by CW should be considered as a preliminary and not complete disinfection treatment. To reuse GW, especially in the irrigation of edible crops, stronger disinfection treatment should be considered as a complement to the preliminary disinfection performed by CW, to avoid any kind of risk. No significant correlation was found for turbidity either as a possible predictor of microbiological contamination or as an influence on biological disinfection.

On the use of extreme value tail modeling for generalized pairwise comparisons with censored outcomes.

In randomized clinical trials, methods of pairwise comparisons such as the 'Net Benefit' or the 'win ratio' have recently gained much attention when interests lies in assessing the effect of a treatment as compared to a standard of care. Among other advantages, these methods are usually praised for delivering a treatment measure that can easily handle multiple outcomes of different nature, while keeping a meaningful interpretation for patients and clinicians. For time-to-event outcomes, a recent suggestion emerged in the literature for estimating these treatment measures by providing a natural handling of censored outcomes. However, this estimation procedure may lead to biased estimates when tails of survival functions cannot be reliably estimated using Kaplan-Meier estimators. The problem then extrapolates to the other outcomes incorporated in the pairwise comparison construction. In this work, we suggest to extend the procedure by the consideration of a hybrid survival function estimator that relies on an extreme value tail model through the Generalized Pareto distribution. We provide an estimator of treatment effect measures that notably improves on bias and remains easily apprehended for practical implementation. This is illustrated in an extensive simulation study as well as in an actual trial of a new cancer immunotherapy.

Identification of suitable areas for African swine fever occurrence in china using geographic information system-based multi-criteria analysis.

African swine fever (ASF) is a hemorrhagic and fatal disease of domestic pigs and wild boars caused by the African swine fever virus (ASFV). There is neither effective treatment nor vaccine at present, and thus this disease has led to major economic losses and adverse impacts on the livelihoods of stakeholders involved in the pork food system in China. In this study, a multi-criteria decision analysis (MCDA) method based on a geographic information system (GIS) was used to identify suitable areas for ASF occurrence in China. Ten spatial risk factors regarding ASF epidemic in China were identified from literature reviews, and the relative importance between them was evaluated by experts based on a pairwise comparison matrix. A numerical weight was calculated for each risk factor using an analytic hierarchy process (AHP) based on the evaluated results. The corresponding geographic data were collected, according to the hypothetical relationship between each factor and the suitability for ASF occurrence, risk factors were converted to standardized geographical layers using suitability relationship and then were combined using a weighted linear combination (WLC) method to produce a map of suitability for ASF occurrence. The results showed that our map has good accuracy in predicting the hot- spots of ASF in China (AUC =0.791; 95% CI [0.741-0.852]). In conclusion, our study provides decision-making aid support for Chinese veterinary services to implement African swine fever surveillance and control measures.

Diversity and Genetic Structure of Scarlet Plume (Euphorbia fulgens), an Endemic Plant of Mexico.

Euphorbia fulgens is an ornamental species cultivated in Europe and endemic to Mexico; its ecological, genetic, and evolutionary aspects are not known. The objectives of this study were to determine its distribution, describe the places it inhabits, and analyze the diversity and genetic structures of wild populations of E. fulgens. A bibliographic review of the herbarium specimens and a field evaluation were carried out to develop a potential distribution map based on a multi-criteria analysis of the climatic and topographic variables. Three populations (forty-five individuals) from pine-oak and cloud forests located in the Southern Sierra of Oaxaca were analyzed using ten microsatellite loci. The analysis was conducted using Arlequin v. 3.5, Mega v. 10, and Structure v. 2.3 programs. Eight loci were polymorphic, and a total of thirty-eight alleles were obtained. The average number of alleles per polymorphic locus was 4.6. The average heterozygosity of the three populations was high (Ho = 0.5483), and genetic differentiation between populations were low, with a high genetic flow, suggesting that it could be an ancestral population that became fragmented and was just beginning to differentiate genetically. The information generated on this restricted distribution species can be used in conservation programs pertaining to human activities that endanger the habitats where it is found.

Erosion susceptibility mapping in the Central-Eastern Region of São Paulo in the last few decades.

Soil degradation has become a critical global environmental challenge as a result of rapid population growth, intensified erosion, and increased global warming. Depletion of nutrients, decreased infiltration, availability of water in the subsoil, silting, and eutrophication of surface water resources are directly associated with soil degradation. Water erosion is one of the primary causes of erosion. The principal objective of this study was to understand how climate change and land use have affected susceptibility to erosion in the central-eastern region of the state of São Paulo, Brazil, over the past few decades. Using the technique of multicriteria decision analysis and comparison of thematic layers in pairs, different factors that contribute to soil erosion were integrated in a GIS environment to map erosion hotspots. The results indicated increasing very high, high, and medium erosion susceptibility class percentage. Slope and soil types were the most sensitive factors; however, changes in land use, in particular, increased land cultivation and expanded areas highly susceptible to erosion in late 2019. The results of this study will assist in implementing soil conservation practices in such areas, reducing soil degradation, and increasing productivity.

Using Structured Decision Making to Evaluate Wetland Restoration Opportunities in the Chesapeake Bay Watershed.

Wetland restoration is an important water quality and climate resilience strategy. Wetland restoration rarely considers tradeoffs at large spatial and temporal scales, which limits capacity to aid decision makers. High resolution data can reveal hundreds to thousands of possible restoration options across a landscape, but guidance for setting restoration targets at these scales is limited. This study uses structured decision making (SDM) as a process for evaluating the desirability of numerous restoration options, with a case study on the Outer Coastal Plain of the Chesapeake Bay watershed, USA. The Nature Conservancy, in partnership with federal, state, and nonprofit organizations, evaluated a decision to target large-scale wetland restoration based on two fundamental objectives: improve water quality and enhance climate resilience. A total of 964 potentially restorable alternatives were delineated across the study area. The alternatives were evaluated on seven water quality and climate resilience criteria. High-priority alternatives were mapped based on multi-criteria ranking methods and principal component analysis. Sensitivity analysis included varying nutrient load data, implementing multiple ranking methods with different assumptions, and varying criteria weights. The maps revealed seven distinct regions of restoration opportunities. Tradeoffs were evaluated to distinguish between desirable and less desirable regions. Results indicated that three regions were promising choices to initiate landowner engagement and outreach. This study highlights the advantages of SDM to structure large-scale restoration decisions. In doing so, our work offers a roadmap toward further developing SDM in future applied restoration contexts.

Evidence-Based User Interface Sanitation Technology Selection for Urban Slums: A Multi-Criteria Analysis; The Case of Jimma Town, Ethiopia.

Slums are urban areas with insufficient public services and access to sanitation. Evidence-based selection of sustainable sanitation options is critical for addressing the sanitation crisis in slums. This mixed methods study was conducted in Jimma Town, southwest Ethiopia, to assess sanitation status and prioritize sustainable sanitation options for slums. The study was done in 2 phases: quantitative and qualitative. The quantitative cross-sectional household survey aimed to assess sanitation status and the qualitative exploratory method to explore alternative sanitation options and prioritize sustainable alternatives. A total of 310 households were chosen using systematic random sampling methods, of which 302 participated. Data was gathered through interviews, which were supplemented with questionnaires and observation checklists, and 2 focus group discussions (FGD) were held. First, FGD was with expertise in the sanitation sector, and the second was with community members. The state of sanitation was summarized, and multi-criteria analysis (MCA) was used to prioritize sustainable sanitation options. According to our findings, 68% of households had access to improved facilities, and 22.5% didn't have any form of toilet facility. About 7 off-site and on-site user interface sanitation technology options were considered in the selection of alternative sanitation technologies, and each option was evaluated against 17 health, economic, social, technical, and environmental criteria. In the final analysis, the options with the highest scores for the setting were flush to septic tanks, compost toilets, and biogas toilets. Mobilizing such a promising sanitation option is recommended for future interventions.

Inter-sectoral prioritization of climate technologies: insights from a Technology Needs Assessment for mitigation in Brazil.

Technological development is key for national strategies to cope with the Paris Agreement's goals. Technology Needs Assessments (TNAs) aim to identify, prioritize, and diffuse climate change mitigation and/or adaptation technologies in developing countries. Their methodology includes a multi-criteria decision analysis (MCDA) framework but, although many countries already conducted a TNA, literature lacks discussions on country-specific processes for a TNA, as it usually follows a one-size-fits-all approach. This paper provides empirical evidence on the importance of country-driven processes that help shaping international programmes into country-specific needs and capabilities. It presents lessons learned from a tailored process for identification, prioritization, and selection of mitigation technologies in the scope of a TNA project for Brazil, an exceptional case of a developing country with strong capacity in integrated assessment modelling (IAM) scenarios for guiding its climate strategies. A previous IAM scenario result allowed pre-selecting technologies in six key economic sectors, while other TNAs prioritized no more than three. This allowed the elaboration of an overall ranking from the MCDA, in contrast to sectoral rankings that are mostly employed in other countries' TNAs. The overall ranking serves not only as a basis for the selection of priority technologies but also provides information on the integrated innovations framework for climate technologies in the country. Further specific findings of the tailored Brazilian TNA approach are discussed in the paper in order to call for the importance that a technology transfer project should not only be country-driven but also conducted through a country-specific process. Supplementary Information: The online version contains supplementary material available at 10.1007/s11027-022-10025-6.