Multi-criteria Analysis Framework Research Articles

Techno-economic feasibility of CO2 utilization for production of green urea by Indian cement industries

The cement industry contributes substantially to global carbon emissions, necessitating urgent adoption of mitigation pathways aligned with climate goals. This study investigates the technical and economic viability of capturing carbon dioxide (CO2) emissions from cement plants in India and using that captured CO2 to produce green urea. The research aims to determine the feasibility of the CCUS approach as a practical way to reduce CO2 emissions from cement production while also boosting India's self-sufficiency in producing urea, a crucial fertilizer. The research uses a multi-criteria analysis (MCA) framework to assess various factors, including the technological readiness of CCUS technologies, the capital and operating costs of setting up and running such a system, the market demand for green urea, and the potential reduction in CO2 emissions. The study focused on 32 major cement plants in India, using data from their annual reports to inform the MCA model with an assumption of a post-combustion Monoethanolamine (MEA) scrubbing capacity CO2 capture capacity of 0.5 million tonnes per year per plant and used existing data and modeling techniques to analyze the feasibility of converting the captured CO2 into urea. The key findings indicate that this approach is promising and projects a 12.4% reduction in CO2 emissions from the cement industry if these 32 plants implement the CCUS technology. Additionally, it highlights a favorable market for the green urea produced, with an estimated output of 21.82 million tonnes per year, enough to offset a significant portion of India's reliance on urea imports. Financially, the study projects a six-year payback period and a 16.7% return on investment. It concludes that implementing CCUS technology to create green urea in Indian cement plants is technically and economically feasible. The approach has the potential to significantly reduce CO2 emissions while also supporting India's goal of self-sufficiency in urea production. However, further investigation and pilot-scale projects are recommended to validate the model's findings and optimize various aspects, such as managing flue gas impurities and leveraging waste heat for energy efficiency.

Designing a sustainable municipal solid waste management system over multiple periods using extended exergy accounting method – a case study of Shanghai

Waste-to-energy technologies can significantly alter urban metabolism and sustainability. This article proposes a multicriteria analysis framework based on the extended exergy accounting method to assess and plan a sustainable municipal solid waste management system from urban metabolism perspective. This framework includes three components. Firstly, an accounting model that integrates material, energy, social, economic, and environmental criteria was developed to identify the contribution of municipal solid waste management system to urban sustainability and to decide whether it is sustainable. Then, a multiperiod municipal solid waste management system planning model was developed to provide the optimal strategy for waste-to-energy facilities deployment and municipal solid waste allocation for different periods. Finally, multidimensional indicators were proposed for a sustainability comparative analysis in overdeployment, pressure on urban ecosystem and urban resource conversion efficiency. The proposed method was applied to the case study of household solid waste management in Shanghai and two scenarios were considered. Our comparison showed that the hybrid scenario (in which various waste recycling technologies were applied together) theoretically performs significantly more sustainable than the incineration scenario in terms of material investment, emissions, economic performance, resource depletion, and recovery. Sensitivity analysis of three parameters—the maximum deployment number of each unit waste-to-energy facility ([Formula: see text]), the minimum utilization rate ([Formula: see text]), and the capacity budget ([Formula: see text])—were carried out. The proposed hybrid method was found to be sensitive to [Formula: see text], but less sensitive to [Formula: see text] and [Formula: see text]. Lessons learnt can be used to plan similar waste-to-energy strategies in other countries.

A comparative multidimensional evaluation of parameters and alternatives for transformation of sustainable cement production in Pakistan

The United Nations has declared its latest climate report a ‘code red,’ sounding the alarm and prompting a global call for scientists and policymakers to adopt comprehensive, systems-wide integrated strategies for promoting sustainable life on Earth. The need for collaborative and holistic approaches for the transformation of cement production into a socio-ecologically sustainable industrial segment had never been more imperative. This paper rigorously evaluates the parameters and alternatives for the sustainable transformation of Pakistan's cement industry. Economic, environmental, and social parameters are explored and screened using multiple methodologies. Real-world data collected from the operating cement plants in Pakistan are analyzed using Principal Component Analysis (PCA) and Grey Relational Analysis (GRA). The consolidated list of sustainability criteria and alternatives is evaluated using the Multi Actor Multi Criteria Analysis (MAMCA) framework, which incorporates the involvement of both local and international stakeholders for prioritization of the transformation goals. Data analytic results reveal that carbon emissions have a strong degree of statistical association with production ingredients such as SiO2, Insoluble Residue (IR), Al2O3, and Fe2O3. Although there are a few interesting variations in the priorities computed from the recorded perspectives of different stakeholders, the consensus on giving top priority to environmental parameters and the alternatives like ‘Waste-heat Recovery Plants’ and ‘Vertical Rolling Mills’ is novel and promising. By taking all the main sustainability domains into account, employing multidimensional techniques, and involving multiple stakeholder perspectives under the context of a developing country, the research outcomes of this study become highly attractive for researchers, investors, and policymakers all over the world.

Systems analysis for energy assets of Iraq influenced by water scarcity

Water security in arid and semi-arid Middle Eastern climates has been severely impacted by effects of climate change such as reduced precipitation, diminished storage, increased evapotranspiration, and prolonged heat waves. These climate effects are compounded in Iraq, where populations, agriculture, industry, and energy rely heavily on varying transboundary water flows to meet water demands. Iraq’s most profitable sector, energy, is especially threatened by insufficient water supply, which complicates government decision making in energy infrastructure development. The goal of this paper is to develop a scenario-based multi-criteria analysis framework to prioritize infrastructure investments in the context of climate change and scarcity of natural resources. Infrastructure facilities are evaluated against social, economic, climate, and hydrologic criteria across a set of disruptive climatological, economic, and social scenarios to identify robust initiatives and the most and least disruptive scenarios to the system. A particular innovation of this paper is the evaluation of hydrology data derived from satellites in determining water scarcity impact on individual energy facilities. The methods are demonstrated for a critical sector of Iraq’s economy: oil and natural gas. The demonstration includes 13 system-order criteria, 44 oil and gas initiatives within Iraq, and seven risk scenarios. The results include an accounting of the most and least disruptive scenarios to energy sector priorities and scenario-based system orderings to guide stakeholders in investment prioritization.

Decision‐making analysis in post‐fire and explosion aftermath assessment tool: A fuzzy cognitive mapping approach

AbstractThis assessment tool was created to generate a decision‐making support system and assessment approach for a post‐fire (aftermath) and blast explosion impact. It uses a multidecision analysis neural network. Multidecision analysis is very crucial as the judgment of the assessment relies not only on engineering input but also on many contributing factors, such as lead time for replacement. This article outlines the framework for post‐incident explosion and fire‐damaged assessment using evaluation acceptance criteria and judgment that streamlines the process. Grounded theory (GT) and fuzzy cognitive mapping (FCM) techniques are presented and evaluated. Overall, this study aims to develop how the project organizations can ensure safety and asset integrity decision‐making by identifying hindrances and later developing a multicriteria analysis framework for the post‐incident assessment phase of implementation.

Decriminalization thresholds for drug possession: A multi-criteria policy analysis framework.

Decriminalization of personal possession of drugs has been proposed as an approach to mitigate the harms of drug prohibition. Despite growing interest, particularly in Canadian settings, analyses of approaches to defining the parameters of what constitutes personal possession within decriminalization models are lacking. Using the Province of British Columbia, Canada, as a case study, we undertook an evidence-based multi-criteria policy analysis of three models for defining personal possession: 1) a model that defines personal possession as the absence of evidence of drug trafficking; 2) a cumulative threshold of 15grams; and 3) a cumulative threshold of 2.5grams. We utilized data from four sources: qualitative interviews with 16 experts, including representatives from government and law enforcement; Vancouver Police drug seizure data; self-reported drug consumption data from longitudinal cohorts of people who use drugs in Vancouver; and publicly available government documents (e.g., the Government of BC's submission for decriminalization). Data was used to identify and define evaluation criteria which reflect the stated policy objectives of decriminalization alongside other policy considerations. This framework was used to conduct a multi-criteria policy analysis of the three different models. The seven evaluation criteria included: 1) reduction in interactions with police; 2) reduction of police drug seizures; 3) coverage for those with high consumption; 4) impact on equity-deserving groups; and acceptance on the part key stakeholders, including: 5) people who use drugs; 6) law enforcement; and 7) the public. The model that performed the best was the cumulative threshold model of 15grams. Findings highlight that different threshold models advance and constrain the stated policy objectives of drug decriminalization to varying degrees. This analysis provides a framework that other jurisdictions considering decriminalization could use to help inform determinations of threshold levels based on stated policy objectives.

Urban sustainability assessment at the neighborhood scale: Integrating spatial modellings and multi-criteria decision making approaches

Urban sustainability is a highly complex concept that requires integrative assessment frameworks to determine the measures that should be adopted to achieve a sustainable city. The present study aimed to conduct a spatially-based sustainability assessment at the neighborhood scale in Isfahan Metropolitan, a rapidly urbanizing region in the center of Iran, using an integrated framework of spatial modeling and multi-criteria decision-making analysis (MCDA). As a first step, the spatial distribution of a set of indicators was provided in three distinct categories, ecosystem service, environmental hazard, and urban structure using various spatial modeling approaches. After standardizing the indicators and assigning appropriate weights to them, different multi-criteria decision analysis models were used to aggregate the indicator layers. The sustainability layers based on ecosystem services, environmental hazards, and urban structure were integrated using MCDA models. The results indicated that less than 3% of the total neighborhood area were categorized as almost sustainable, while 36.1% and 59.4% were respectively scored as poor and moderate sustainable area. None of the neighborhoods was categorized in the sustainably good class, whereas 1.73% of the area was unsustainable. Moreover, the urban structure-based aspect was found to be the most sustainable, while the urban environmental hazards dimension exhibited the lowest sustainability, with 71.98% falling into the poor and unsustainable category. The spatial investigation showed that the central parts of the city were more sustainable than the urban periphery. In conclusion, a spatially-based sustainable assessment of Isfahan City at the neighborhood level can provide urban planners with valuable insights to undertake operational actions and achieve sustainable development goals.

Solid Waste Landfill Site Assessment Framework Based on Single-Valued Neutrosophic Hybrid Aggregation and Multi-Criteria Analysis

Landfills are an effective way to dispose of waste and appropriate landfill sites can lessen environmental damage during waste treatment. Solid waste landfill site (SWLS) selection has received much attention in the area of multi-criteria decision-making in recent years. However, the uncertainty and complexity of the SWLS selection make it a significant challenge for decision makers (DMs). Since single-valued neutrosophic (SVN) sets have the great advantage of handling complex problems with uncertain and inconsistent information, this paper aims at offering a site planning strategy under the SVN environment. For the SWLS selection problem with interrelated factors, the Schweizer–Sklar power Bonferroni mean operator is first created, which not only considers the possible correlations among attributes but also reduces the adverse effects of anomalous assessment information on decision results. Then, a multi-criteria analysis framework based on the aggregation operator is proposed and then applied to a real-world SWLS selection. DMs can flexibly adjust the parameters in this model to achieve a preferred SWLS that integrates economic, environmental, and social perspectives. The consistent results obtained from the comparative analysis highlight its benefits for selecting proper SWLSs.

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.

Urban flood susceptibility analysis of Saroor Nagar Watershed of India using Geomatics-based multi-criteria analysis framework.

During the monsoon season, flooding is common in several parts of India, and urban areas are becoming more prone to flooding even during less intense rainfall events as a result of the encroachment of waterbodies and natural drainage channels, increased impervious areas, and subsequent decrease in infiltration capabilities. In the years 2000, 2008, 2016, 2019, 2020, and 2021, severe flood events in our study area, the Saroor Nagar urban watershed in Telangana state, caused human loss, economic devastation, and environmental devastation. Although flood risk cannot be completely eliminated, it can be significantly reduced by developing a flood hazard model to identify flood-prone areas in a watershed, which can assist decision makers seeking comprehensive flood risk management. The flood hazard map is created by integrating Geomatics with multi-criteria decision analysis and the analytical hierarchy process (AHP). Topographic wetness index (TWI), digital elevation model (DEM), slope, precipitation, drainage density, distance to waterbody, soil, and land use land cover (LULC) were the flooding causative elements considered in this study. The resulting flood risk map is divided into four distinct categories that reflect flood danger levels of low, moderate, high, and extremely high. The flood risk map revealed that the moderate risk zone decreased from 50.2 to 45.7% of the study area between 2008 and 2020, while the high-risk zone increased from 45.2 to 52.8%. The flood susceptibility map is validated using crowdsourcing techniques. The findings demonstrated that a Geographic Information System (GIS)-based multi-criteria analysis framework for flood hazard analysis could be effectively used to aid disaster management decision-making.

A multi-criteria analysis framework for conflict resolution in the case of offshore wind farm sitting: A study of England and the Netherlands offshore space

Growing EU energy ambitions in the North Sea region are urging for an accelerated deployment of large-scale renewable energy (RE) infrastructure, with offshore wind farms (OWF) playing an essential role. However, implementing the current EU targets is limited by the competing spatial claims between existing sea uses and OWFs and uncertainties related to potential risks of interaction, creating important barriers to a swift roll-out of RE infrastructure. In tackling this issue, we are proposing a transparent and spatially explicit multi-criteria analysis tool to quantify and qualify the main risks and opportunities resulting from the interaction between OWFs and four other seas user groups (shipping, marine protected areas, fisheries and military activities). The multi-criteria analysis framework is accounting for sectoral activity specific risks of interaction with OWFs, classified through the respective available conflict resolution options, which allows for the quantification of the average conflict score (ACS) between the selected activities and OWFs. Using the resulting ACS and the geo-location of areas of interaction, we map areas of high and low conflict with OWFs and indicate management options for solving, minimizing or compensating the conflicts. Our results indicate that conflict resolution strategies in marine mammal’s habitats present the highest potential for unlocking medium value OWF sites both for the Dutch case (15.8 – 28 GWs) and English case (15.94-28.3 GWs), followed by pelagic fisheries in the Dutch case (15-26.9 GWs) and passenger/cargo routes in the English case (10.9-19.4 GWs). The strategic planning of increasingly larger and more complex OWF projects will require a better understanding not only of the level of conflict with the other sea users in relation to the valuable OWF sites, but also potential management options to solve, minimize or compensate those conflicts. As an example, accessing 6.8-12.3 GWs in high value OWF sites in the Dutch EEZ will require the relocating of military flying areas with forbidden access, while technical solutions such as “fill-in-the-gap” or relocation of lower airspace radars could unlock 10.25-18.16 GWs in the English EEZ. By avoiding high risk areas and prioritizing areas of low conflict, the bottlenecks, negative effects and inefficiencies related to space management options can be minimized, while synergies and positive effects of OWF deployment can be timely captured.

Building smart living environments for ageing societies: Decision support for cross-border e-services between Estonia and Finland

Rapidly aging societies are exerting pressure on the public and private sectors to provide e-services as integral parts of age-friendly smart living environments (SLEs). It is also recognized that interoperable cross-border e-services can reduce this societal challenge, particularly in more ‘individualistic’ countries in Northern and Western Europe such as Estonia and Finland. This study primarily provides decision support for multiple stakeholders involved in the development and provision of interoperable cross-border e-services and related cross-border data exchange between Estonia and Finland. Given the high complexity of the research questions, this study adopted a constructivist, sociotechnical approach that combined cognitive mapping and the decision-making trial and evaluation laboratory (DEMATEL) technique. Based on two real-world cases, data were collected from two panels of experts who represented regional stakeholders involved in building e-services and age-friendly SLEs in Estonia and Finland. The study results include a multicriteria analysis framework of the context factors and recommendations for determining effective intervention strategies.

Site suitability analysis of indigenous rainwater harvesting systems in arid and data-poor environments: a case study of Sana’a Basin, Yemen

Indigenous rainwater harvesting (RWH) is a promising tool for increasing water availability and conserving groundwater in arid environments. This study aimed to develop a multicriteria analysis (MCA) framework to identify and rank suitable sites for different indigenous RWH systems in data-poor areas taking Sana’a Basin, Yemen, as a case study. Unlike previous research, this study focused only on indigenous RWH systems and, for the first time, considered the site suitability analysis of spate irrigation systems. Five biophysical and six socioeconomic criteria were used to select, prioritize, and map suitable zones for indigenous RWH systems. This study, the first to be conducted in Yemen, found that more than 30% of the case area has a high or very high level of suitability for each of the studied RWH systems. Only 11% to 17% of the area is not suitable for RWH due to socioeconomic activities. Twenty-four percent of the area was considered moderately suitable, and 28% had a low level of suitability for RWH. These results are promising, and the preliminary identification process of suitable areas for indigenous RWH systems is a useful guide for future water resource and land management programs.Graphical abstract

A GIS-Based Multi-Criteria Analysis Framework to Evaluate Urban Physical Resilience against Earthquakes

As complex man-made systems that are home to the majority of the world population, cities have always faced a wide range of risks such as earthquakes. As the backbone of urban systems, physical components, including buildings, transportation networks, communication networks, and open and green spaces, are also vulnerable to disasters. To enhance the capacity to deal with disaster risks, enhancing urban resilience has recently become an essential priority for cities. This study aims to develop and pilot test a framework to evaluate urban physical resilience based on resilience characteristics and associated physical indicators. Interpretive Structural Modelling (ISM) was used to determine the relationships between physical indicators, and Multi-Criteria Decision-Making methods were applied to determine the relative importance of the characteristics. The results showed that the ‘Robustness of Building’, ‘Building Density’, ‘Aspect Ratio’, and ‘Street Width’ are the most important among the twenty physical indicators considered in the proposed framework. Subsequently, the proposed framework was applied to one of the districts of Kerman, a major city located in the southwest, earthquake-prone part of Iran. Overall results indicate low levels of physical resilience. The findings of this study can provide urban planners and decision-makers with more transparent and practical insights into the physical resilience of cities. Results can also be used to design and implement policies and programs to improve the current conditions.

A novel methodology for micromobility system assessment using multi-criteria analysis

With cities around the world increasingly looking at micromobility as a means to achieve their goals for cleaner transportation and better air quality, local authorities, planners, and shared mobility operators are increasingly confronted with decision problems related to investment in micromobility systems. In order for decision making to be better informed, and objectives to be achieved, prioritizing investment according to the area needs and characteristics is highly important. In this context, the objectives of the present study are two: (1) propose a framework for the evaluation of neighborhood suitability for micromobility modes, (2) assist decision making with regards to the selection of the optimal micromobility system type for a study area. First, considering a range of both supply- and demand-based criteria, we construct an index calculated using a weighted multi-criteria approach with the purpose of identifying neighborhoods that are more conducive or less conducive to the integration of micromobility. Relative weights of the criteria and the respective indicators used for the calculation of the index are derived through the Analytic Hierarchy Process (AHP) method. The developed assessment framework is applied in three case studies of different scale: an urban district in the center of Paris, a university campus in the southern suburbs, and an eco-district currently under development in the southwestern suburbs of the city. Then, in the context of the second objective of this work, we propose a multi-criteria analysis framework for the selection of the optimal system type among seven alternative options for each study area. Considering multiple factors associated with the desirability of each of these modes in a neighborhood, we calculate priorities for each system type for the three selected case studies, using the classical AHP method.

Implementation of a multicriteria analytical framework for the sustainability evaluation and comparison of concrete materials considering methodological uncertainties

Multicriteria analysis (MCA) is one practical tool to support sustainability decision-making processes considering numerous evaluation criteria. Its conventional analytical stages include the selection of indicators, normalization, weighting, and aggregation. The decisions based on conventional MCA stages, however, could be subject to criticism and bias because each analytical stage can be performed in a multiple number of ways, creating methodological uncertainties which ultimately lead to uncertainty in the MCA output. This paper tackles how to address methodological uncertainties objectively through a practical implementation of an MCA framework for sustainability evaluation under uncertainty. The implementation is demonstrated by a concrete material selection problem, wherein the sustainability performance of different ready-mix concretes are compared, and the “most sustainable” alternative is identified. The unique characteristics of the framework are the use of uncertainty and sensitivity analyses, which transform the results to a probabilistic form, and provide quantitative measures for the objective management of methodological uncertainties. Due to the stochastic nature of the result, a probabilistic tool to hierarchically order the concrete mixes according to their sustainability performance is also developed. This facilities the identification of the “most sustainable” alternative concrete mix while also considering the level of uncertainty associated with that result, thus highlighting the applicability of the framework to support sustainable decision-making under methodological uncertainties.

A hybrid Delphi-AHP multi-criteria analysis of Moving Block and Virtual Coupling railway signalling

The railway industry needs to investigate overall impacts of next generation signalling systems such as Moving Block (MB) and Virtual Coupling (VC) to identify development strategies to face the forecasted railway demand growth. To this aim an innovative multi-criteria analysis (MCA) framework is introduced to analyse and compare VC and MB in terms of relevant criteria including quantitative (e.g. costs, capacity, stability, energy) and qualitative ones (e.g. safety, regulatory approval). We use a hybrid Delphi-Analytic Hierarchic Process (AHP) technique to objectively select, combine and weight the different criteria to more reliable MCA outcomes. The analysis has been performed for different rail market segments including high-speed, mainline, regional, urban and freight corridors. The results show that there is a highly different technological maturity level between MB and VC given the larger number of vital issues not yet solved for VC. The MCA also indicates that VC could outperform MB for all market segments if it reaches a comparable maturity and safety level. The provided analysis can effectively support the railway industry in strategic investment planning of VC.

Development and integrated assessment of the circular economy in the European Union: the outranking approach

Purpose The Green Deal strategy of the European Union (EU) as well as the increasing concerns over resource scarcity worldwide has put forward such concepts as the circular economy. This paper seeks to compare the progress of the development of the circular economy across the EU Member States. Such analysis is helpful in guiding the circular economy support policies. Design/methodology/approach This paper develops a quantitative framework for analysis of the implementation of the circular economy objectives in the EU Member States. The framework proposed includes three multi-criteria decision making methods representing reference point and outranking approaches. The use of multiple methods allows exploiting the differences in the underlying aggregation principles. Findings Germany, Sweden and the Netherlands appear as the most advanced in the sense of circular economy development. The results indicate that the water-locked small countries and the new EU Member States are among the lowest performing ones. The flows of the waste need to be monitored more tightly in order to increase the circularity. The development of recycling facilities can also increase circularity irrespectively of the economic development level (e.g. the case of Bulgaria). Originality/value The paper contributes to the discussion regarding the circular economy by proposing an indicator system and the multi-criteria analysis framework. The proposed indicator system covers input use (circularity), trade flows and recycling processes. The proposed framework can be applied to track the progress of different countries in implementing the targets of the circular economy.

GIS Based Forest Fire Vulnerability Assessment and its Validation using field and MODIS Data: A Case Study of Bhaderwah Forest Division, Jammu and Kashmir (India)

The present study assesses the forest fire vulnerability of the Bhaderwah forest division in the UT of Jammu and Kashmir. The vibrant green forests of the Bhaderwah forest division play an essential role in preventing soil erosion, maintaining the ecological balance and serves as habitat for wildlife. In efforts to nurture the rich biodiversity, it is essential to manage this forest division using modern scientific technology for fire protection. The present study makes the use of MODIS fire data related to the field point data of forest fires in a multi-criteria analysis (MCA) framework to assess the fire vulnerability of Bhaderwah Forest Division using Geographical Information System (GIS). In the present study, land use, vegetation, topographical parameters, and human influence parameters are used as inputs to the multi-criteria analysis for dividing the study area based on sensitivity to forest fires. The outcome from the present study reports that out of the total 342 compartments of Bhaderwah Forest Division, 187 compartmentsfall in high vulnerability zone, 123 compartmentsfall in medium vulnerability zone, whereas only 32 compartments fall in low vulnerability zone. The present study can be constructive in formulating better strategies to combat forest fires in the area.

Incorporating stakeholders\u2019 preferences into a multi-criteria framework for planning large-scale Nature-Based Solutions

Hydro-meteorological risks are a growing issue for societies, economies and environments around the world. An effective, sustainable response to such risks and their future uncertainty requires a paradigm shift in our research and practical efforts. In this respect, Nature-Based Solutions (NBSs) offer the potential to achieve a more effective and flexible response to hydro-meteorological risks while also enhancing human well-being and biodiversity. The present paper describes a new methodology that incorporates stakeholders’ preferences into a multi-criteria analysis framework, as part of a tool for selecting risk mitigation measures. The methodology has been applied to Tamnava river basin in Serbia and Nangang river basin in Taiwan within the EC-funded RECONECT project. The results highlight the importance of involving stakeholders in the early stages of projects in order to achieve successful implementation of NBSs. The methodology can assist decision-makers in formulating desirable benefits and co-benefits and can enable a systematic and transparent NBSs planning process.