An expert-based approach to forest road network planning by combining Delphi and spatial multi-criteria evaluation

Changes in forest landscapes resulting from road construction have increased remarkably in the last few years. On the other hand, the sustainable management of forest resources can only be achieved through a well-organized road network. In order to minimize the environmental impacts of forest roads, forest road managers must design the road network efficiently and environmentally as well. Efficient planning methodologies can assist forest road managers in considering the technical, economic, and environmental factors that affect forest road planning. This paper describes a three-stage methodology using the Delphi method for selecting the important criteria, the Analytic Hierarchy Process for obtaining the relative importance of the criteria, and finally, a spatial multi-criteria evaluation in a geographic information system (GIS) environment for identifying the lowest-impact road network alternative. Results of the Delphi method revealed that ground slope, lithology, distance from stream network, distance from faults, landslide susceptibility, erosion susceptibility, geology, and soil texture are the most important criteria for forest road planning in the study area. The suitability map for road planning was then obtained by combining the fuzzy map layers of these criteria with respect to their weights. Nine road network alternatives were designed using PEGGER, an ArcView GIS extension, and finally, their values were extracted from the suitability map. Results showed that the methodology was useful for identifying road that met environmental and cost considerations. Based on this work, we suggest future work in forest road planning using multi-criteria evaluation and decision making be considered in other regions and that the road planning criteria identified in this study may be useful.     

A combined ANP-delphi approach to evaluate sustainable tourism

The evaluation of sustainable tourism strategies promoted by National Parks (NP) related stakeholders is a key concern for NP managers. To help them in their strategic evaluation procedures, in this paper we propose a methodology based on the Analytic Network Process and a Delphi-type judgment-ensuring procedure. The approach aims at involving stakeholders in a participatory and consensus-building process.The methodology was applied to Los Roques NP in Venezuela. The problem included three sustainable tourism strategies defined by the stakeholders: eco-efficient resorts, eco-friendly leisure activities and ecological transportation systems. Representatives of eight stakeholders participated in the methodology. 13 sustainability criteria were selected.Results provide some important insights into the overall philosophy and underlying participants' conception of what sustainable development of Los Roques NP means. This conception is broadly shared by stakeholders as they coincided in the weights of most of the criteria, which were assigned individually through the questionnaire. It is particularly noteworthy that tourists and environmentalists almost fully match in their assessments of criteria but not of the alternatives.Moreover, there is a great agreement in the final assessment. This suggests that the regular contact among the different stakeholders, i.e. tourists with inhabitants, authorities with environmentalists, tour operators with representatives of the ministry, etc. has led to a common understanding of the opportunities and threats for the NP.They all agreed that the procedure enhances participation and transparency and it is a necessary source of information and support for their decisions.     

Multi-criteria decision analysis with probabilistic risk assessment for the management of contaminated ground water

Traditionally, environmental decision analysis in subsurface contamination scenarios is performed using cost–benefit analysis. In this paper, we discuss some of the limitations associated with cost–benefit analysis, especially its definition of risk, its definition of cost of risk, and its poor ability to communicate risk-related information. This paper presents an integrated approach for management of contaminated ground water resources using health risk assessment and economic analysis through a multi-criteria decision analysis framework. The methodology introduces several important concepts and definitions in decision analysis related to subsurface contamination. These are the trade-off between population risk and individual risk, the trade-off between the residual risk and the cost of risk reduction, and cost-effectiveness as a justification for remediation. The proposed decision analysis framework integrates probabilistic health risk assessment into a comprehensive, yet simple, cost-based multi-criteria decision analysis framework. The methodology focuses on developing decision criteria that provide insight into the common questions of the decision-maker that involve a number of remedial alternatives. The paper then explores three potential approaches for alternative ranking, a structured explicit decision analysis, a heuristic approach of importance of the order of criteria, and a fuzzy logic approach based on fuzzy dominance and similarity analysis. Using formal alternative ranking procedures, the methodology seeks to present a structured decision analysis framework that can be applied consistently across many different and complex remediation settings. A simple numerical example is presented to demonstrate the proposed methodology. The results showed the importance of using an integrated approach for decision-making considering both costs and risks. Future work should focus on the application of the methodology to a variety of complex field conditions to better evaluate the proposed methodology.     

Circular economy application for a Green Stadium construction towards sustainable FIFA world cup Qatar 2022™

The construction industry is responsible for a significant amount of raw material consumption and environmental footprints. Therefore, sustainable construction became a hot topic, which strives to reduce material consumption, limit constructional waste disposal, and decrease contribution to climate change. In line with Qatar's commitment to organizing a sustainable FIFA World Cup in 2022, this study aims to conduct an environmental life cycle assessment (LCA) for the construction of the Education City Stadium. The work presented here provides the first empirical LCA for analyzing the environmental and economic impacts of circular economy application in a World Cup stadium. In this research, the cyclopean concrete (CYC) methodology was utilized, which incorporate the site excavated boulders with the concrete mix to cast the under-raft foundation of the stadium. This approach was compared to the conventional concrete (CC) casting approach to assess the extent to which the newly developed methodology can reduce the environmental and economic burdens. The obtained results have shown a 32% reduction in greenhouse gas emissions when adapting the CYC approach. Thus, the CYC holds a strong promise to achieve the required structural behavior with a low-cost alternative material from existing waste products in Qatar and a lower environmental impact than the CC.     

An Integrated Multicriteria Decision Analysis System for Reducing Air Emissions from Mining Process

The selection of a best alternative method to minimize air pollution and energy consumption for mine sites is a critical task because it encompasses evaluation of different techniques. The aim of this paper is to select most suitable technology for mining system which helps in reducing air pollution and carbon footprints by implementing the multicriteria decision analysis (MCDA) method. The existing methods or frameworks in the mining sector, which have been used in the past to select the sustainable solution, are lacking aid of MCDA, and there is a need to contribute more in this field with a promising decision system. The MCDA method is applied as a probabilistic integrated approach for a mine site in Canada. The analysis involves processing inputs to the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) method which assists in identifying the alternatives, defining the criteria, and thus outranking of the final choice. Moreover, criteria weighting has been determined using analytical hierarchical process (AHP) method. Three categories: reduction of dust/fugitive emission control strategies, reduction in fuel consumption to minimize carbon footprint, and cyanide destruction methods are selected. The probability distributions of criteria weights and output flows are defined by performing uncertainty analysis using the Monte Carlo simulation (MCS). The sensitivity analysis is conducted using Spearman’s rank correlation method and walking criteria weights. The results indicate that the integrated framework provides a reliable way of selecting air pollution control solutions and help in quantifying the impact of different criteria for the selected alternatives.

     

Application of analytic hierarchy process in a waste treatment technology assessment in Mexico

The high per capita generation of solid waste and the environmental problems in major rural communities of Ensenada, Baja California, have prompted authorities to seek alternatives for waste treatment. In the absence of a selection methodology, three technologies of waste treatment with energy recovery (an anaerobic digester, a downdraft gasifier, and a plasma gasifier) were evaluated, taking the broader social, political, economic, and environmental issues into considerations. Using the scientific literature as a baseline, interviews with experts, decision makers and the community, and waste stream studies were used to construct a hierarchy that was evaluated by the analytic hierarchy process. In terms of the criteria, judgments, and assumptions made in the model, the anaerobic digester was found to have the highest rating and should consequently be selected as the waste treatment technology for this area. The study results showed low sensitivity, so alternative scenarios were not considered. The methodology developed in this study may be useful for other governments who wish to assess technologies to select waste treatment.     

An Analytic Network Process approach for the environmental aspect selection problem — A case study for a hand blender

Life Cycle Assessment is a tool to assess, in a systematic way, the environmental aspects and its potential environmental impacts and resources used throughout a product's life cycle. It is widely accepted and considered as one of the most powerful tools to support decision-making processes used in ecodesign and sustainable production in order to learn about the most problematic parts and life cycle phases of a product and to have a projection for future improvements. However, since Life Cycle Assessment is a cost and time intensive method, companies do not intend to carry out a full version of it, except for large corporate ones. Especially for small and medium sized enterprises, which do not have enough budget for and knowledge on sustainable production and ecodesign approaches, focusing only on the most important possible environmental aspect is unavoidable. In this direction, finding the right environmental aspect to work on is crucial for the companies. In this study, a multi-criteria decision-making methodology, Analytic Network Process is proposed to select the most relevant environmental aspect. The proposed methodology aims at providing a simplified environmental assessment to producers. It is applied for a hand blender, which is a member of the Electrical and Electronic Equipment family. The decision criteria for the environmental aspects and relations of dependence are defined. The evaluation is made by the Analytic Network Process in order to create a realistic approach to inter-dependencies among the criteria. The results are computed via the Super Decisions software. Finally, it is observed that the procedure is completed in less time, with less data, with less cost and in a less subjective way than conventional approaches.     

LCA Integrated ANP Framework for Selection of Sustainable Manufacturing Processes

In recent times, the focus of sustainable development has been shifted toward the process domain to achieve greater environmental benefits. Improved sustainability in the process domain can be achieved by selecting sustainable process or through improvement studies. In this study, sustainability performance of injection molding (IM) and selective laser sintering (SLS) processes are compared to select the sustainable process. Life cycle assessment (LCA) has been widely accepted for assessing the environmental performance of manufacturing process. However, the problem with LCA is the interpretation of impact category scores when comparing alternate processes. Therefore, an effort has been made to integrate analytical network process (ANP) methodology with LCA in which LCA methodology calculates the impact score and ANP computes the Single Point Process Sustainability Score (SPPSS) to compare alternate processes. Based on the inventory data collected for higher production rates, SPPSS for IM and SLS processes are computed as 0.038 and 0.068, respectively. Based on the score, IM has been identified as a sustainable process for higher production volume. Hence, the practical usability of the proposed methodology is validated by the study. This study also appreciates the application of ANP along with LCA for decision making in the real-time scenario.     

Bridging the divide between theory and guidance in strategic environmental assessment: A path for Italian regions

Clear and effective legislation is a requisite to bring sustainable development from theory into practice. This paper develops a methodology to investigate how Italian regional legislation disciplines the use of Strategic Environmental Assessment (SEA), the procedure used in the European Union (EU) to pursue sustainable development of policies, plans, and programs (PPPs). Our case study is the Italian regional level, examined to identify eventual flaws and areas for improvement for each regional legislative framework. For this purpose, this study refers to a selection of analytical criteria recurring in the international debate on sustainability assessments. Statistical multi-dimensional analysis is used to identify Italian regions with similar SEA legislation. We recognize four taxonomies, depending on the way regional legislation provides information about i) legislation and guidelines, ii) integration between SEA and PPPs, iii) sustainability goals, iv) technical organization, v) participatory organization, and vi) monitoring. The results suggest that Italian administrators should cooperate to improve legislation at the regional level. Acknowledging the institution-centred nature of SEA, this methodology could drive the EU to better support SEA development in countries with diversified traditions.     

Analysis of spatio-temporal land cover changes for hydrological impact assessment within the Nyando River Basin of Kenya

The spatio-temporal changes in the land cover states of the Nyando Basin were investigated for auxiliary hydrological impact assessment. The predominant land cover types whose conversions could influence the hydrological response of the region were selected. Six Landsat images for 1973, 1986, and 2000 were processed to discern the changes based on a methodology that employs a hybrid of supervised and unsupervised classification schemes. The accuracy of the classifications were assessed using reference datasets processed in a GIS with the help of ground-based information obtained through participatory mapping techniques. To assess the possible hydrological effect of the detected changes during storm events, a physically based lumped approach for infiltration loss estimation was employed within five selected sub-basins. The results obtained indicated that forests in the basin declined by 20% while agricultural fields expanded by 16% during the entire period of study. Apparent from the land cover conversion matrices was that the majority of the forest decline was a consequence of agricultural expansion. The model results revealed decreased infiltration amounts by between 6% and 15%. The headwater regions with the vast deforestation were noted to be more vulnerable to the land cover change effects. Despite the haphazard land use patterns and uncertainties related to poor data quality for environmental monitoring and assessment, the study exposed the vast degradation and hence the need for sustainable land use planning for enhanced catchment management purposes.     

Genetic Algorithm Usage in Water Quality Monitoring Networks Optimization in Gediz (Turkey) River Basin

Selection procedure of the optimum station combination for decreasing the station number from 33 to 14 in water quality monitoring network of Gediz river basin was applied using an optimization method. Gediz basin is one of the important basins and it covers 2.3% of the total surface area of Turkey. The technique includes two stages as the data preparation and the optimization. In the data preparation stage, firstly, alternative station combinations decreased and then station combination scores obtained from assigned selection criteria for point and nonpoint pollution management objectives. Finally, genetic algorithm applied to select the best combination. The results were compared with a prior solution that used dynamic programming as the optimization technique.     

Uncertainty based optimal monitoring network design for a chlorinated hydrocarbon contaminated site

An application of a newly developed optimal monitoring network for the delineation of contaminants in groundwater is demonstrated in this study. Designing a monitoring network in an optimal manner helps to delineate the contaminant plume with a minimum number of monitoring wells at optimal locations at a contaminated site. The basic principle used in this study is that the wells are installed where the measurement uncertainties are minimum at the potential monitoring locations. The development of the optimal monitoring network is based on the utilization of contaminant concentration data from an existing initial arbitrary monitoring network. The concentrations at the locations that were not sampled in the study area are estimated using geostatistical tools. The uncertainty in estimating the contaminant concentrations at such locations is used as design criteria for the optimal monitoring network. The uncertainty in the study area was quantified by using the concentration estimation variances at all the potential monitoring locations. The objective function for the monitoring network design minimizes the spatial concentration estimation variances at all potential monitoring well locations where a monitoring well is not to be installed as per the design criteria. In the proposed methodology, the optimal monitoring network is designed for the current management period and the contaminant concentration data estimated at the potential observation locations are then used as the input to the network design model. The optimal monitoring network is designed for the consideration of two different cases by assuming different initial arbitrary existing data. Three different scenarios depending on the limit of the maximum number of monitoring wells that can be allowed at any period are considered for each case. In order to estimate the efficiency of the developed optimal monitoring networks, mass estimation errors are compared for all the three different scenarios of the two different cases. The developed methodology is useful in coming up with an optimal number of monitoring wells within the budgetary limitations. The methodology also addresses the issue of redundancy, as it refines the existing monitoring network without losing much information of the network. The concept of uncertainty-based network design model is useful in various stages of a potentially contaminated site management such as delineation of contaminant plume and long-term monitoring of the remediation process.     

Adsorption of the antiepileptic carbamazepine onto agricultural soils

Carbamazepine is an antiepileptic pharmaceutical which is commonly found in environmental matrices. It passes through wastewater treatment plants (WWTPs) almost completely unaffected and has been found to be highly persistent in the environment. The application of sludge in agricultural fields and the use of WWTP effluents for irrigation constitute a potential source of soil contamination. Consequently, the assessment of the interaction between carbamazepine and soils is of crucial importance to understand its fate in the environment. To monitor the sorption behavior of carbamazepine onto agricultural soils, batch equilibrium experiments were performed using soils subjected to distinct long-term fertilizations. In order to follow the adsorption experiments, an UV spectral deconvolution methodology was applied and the results compared with those from micellar electrokinetic chromatography. The results obtained by both methods did not present significant statistical differences at 95% confidence level. Therefore, it was proven that, in the context of adsorption studies, UV spectral deconvolution is a valid alternative to common chromatographic methods, with the major advantage of being a simple and fast procedure. The adsorption of carbamazepine onto the selected soils was satisfactorily described by the Freundlich model. The obtained Freundlich parameters (K(F)) (between 1.79 ± 0.07 and 4.8 ± 0.2 mg kg(-1) (mg L(-1))(-N)) indicate that the adsorption behavior of carbamazepine is dependent on the soil fertilization. Also, it is not extensively sorbed, indicating that carbamazepine present in soils can be a potential source of contamination of surface and ground waters through run-off and infiltration.     

Community Exchange and Training in the Suid Bokkeveld: A UNCCD Pilot Project to Enhance Livelihoods and Natural Resource Management

Community knowledge exchanges have played a key role in developmental processes in the Suid Bokkeveld community of South Africa. Two exchange visits were undertaken with the support of the Department of Agriculture and an NGO, the Environmental Monitoring Group, which have led to local economic development and enhanced capacity to manage natural resources in a sustainable manner. These pilot projects were undertaken within the framework of the Community Exchange and Training Programme of the Global Mechanism of the United Nations Convention to Combat Desertification (UNCCD). The methodology applied included facilitation to develop a community-based vision for development, in terms of which the community exchange process was designed. A Facilitation Team of service providers conducted preparatory workshops, and identified potential partner communities. Two exchange visits were carried out, one focused on Rooibos production and marketing, and the other on community-based eco-tourism. Following report-back and planning workshops, emerging community-driven initiatives were supported through their formative stages. The initiatives have not only resulted in enhanced livelihoods, but the methodology has also been applied widely in a number of different contexts.     

Applying the grey assessment to the evaluation system of ecological green space on greening projects in Taiwan

This study is designed to develop an alternative evaluation method for ecological green space. It offers criteria for identifying ecological green space on building sites. The grey decision-making method is applied to assess the greening project at the first step. The evaluation items are rebuilt by the analytic hierarchy process (AHP) method at the second step. The range of standard values and the weighting values are also obtained by AHP. Grey classes are identified using the whitening weight function of the grey number. The evaluation system of the ecological green space is framed by grey clusters. We considered the factors of building environment and the scale of building sites in the ecological greenery of green building sites.This study proposes a new model to solve the problems hard to be quantified. Especially for those ecological benefits are too close to decide. Architects and landscape architects can input the engineering data and the design information into the ecological greenery assessment system. The identification and assessment system of green space is fit for Taiwan area. We will obtain the best greening project by the maximum value of absolute degree of grey incidence (max{varepsilon ( ij )}) in grey-decision making. The maximum value of synthetic clustering coefficient (max{sigma ( k )}) in grey clustering assessment reflects the quality and variation of green space.     

The burning of fuelwood in South Africa: When is it sustainable?

Fuelwood harvesting is considered sustainable when consumption is equal to or less than production. An empirical model was developed to estimate potential fuelwood production from savannas. The model is based on the observation that in semiarid savannas, biomass production is linearly dependent on rainfall. Woody basal area is linked to mean annual precipitation, and aboveground woody biomass is proportional to basal area. Production averages 4% of standing woody biomass and is corrected to exclude stems that are too small for harvesting. The model assumes that the entire area consists of seminatural savanna. Corrections for the land lost as a result of land transformation and degradation would have to be included. Data on land loss can most effectively be obtained from satellite imagery, with appropriate ground calibration. The model is based on limited data sets but in most instances has been validated against independently collected data. The model yields a reasonable prediction at a national and regional level, but estimates for limited areas or specific points on the ground may differ substantially from the predicted values. Model results indicate a potential for sustainable fuelwood production at the national level, but specific regions are using fuelwood at nonsustainable levels.     

Strategic environmental assessment for sustainability: A review of a decade of academic research

This paper examines the strategic environmental assessment (SEA)–sustainability relationship over the past decade, from 2000 to 2010, focusing in particular on the incorporation of sustainability in SEA. A total of 86 papers from the academic literature containing the terms ‘sustainability’ or ‘sustainable development’ and ‘strategic environmental assessment’ were identified and reviewed. Several common themes emerged by which SEA can support sustainability, including providing a framework to support decision making for sustainability; setting sustainability objectives, ensuring the consideration of ‘more sustainable’ alternatives, and integrating sustainability criteria in PPP development; and promoting sustainability outcomes through tiering and institutional learning. At the same time, our review identified many underlying barriers that challenge SEA for sustainability, including the variable interpretations of the scope of sustainability in SEA; the limited use of assessment criteria directly linked to sustainability objectives; and challenges for decision-makers in operationalizing sustainability in SEA and adapting PPP development decision-making processes to include sustainability issues. To advance SEA for sustainability there is a need to better define the scope of sustainability in SEA; clarify how to operationalize the different approaches to sustainability in SEA, as opposed to simply describing those approaches; provide guidance on how to operationalize broad sustainability goals through assessment criteria in SEA; and understand better how to facilitate institutional learning regarding sustainability through SEA application.     

Selection of suitable alternatives to reduce the environmental impact of road traffic noise using a fuzzy multi-criteria decision model

Road traffic noise is one of the most significant environmental impacts generated by transport systems. To this regard, the recent implementation of the European Environmental Noise Directive by Public Administrations of the European Union member countries has led to various noise action plans (NAPs) for reducing the noise exposure of EU inhabitants. Every country or administration is responsible for applying criteria based on their own experience or expert knowledge, but there is no regulated process for the prioritization of technical measures within these plans. This paper proposes a multi-criteria decision methodology for the selection of suitable alternatives against traffic noise in each of the road stretches included in the NAPs. The methodology first defines the main criteria and alternatives to be considered. Secondly, it determines the relative weights for the criteria and sub-criteria using the fuzzy extended analytical hierarchy process as applied to the results from an expert panel, thereby allowing expert knowledge to be captured in an automated way. A final step comprises the use of discrete multi-criteria analysis methods such as weighted sum, ELECTRE and TOPSIS, to rank the alternatives by suitability. To illustrate an application of the proposed methodology, this paper describes its implementation in a complex real case study: the selection of optimal technical solutions against traffic noise in the top priority road stretch included in the revision of the NAP of the regional road network in the province of Almeria (Spain).     

The contribution of sensor-based equipment to life cycle assessment through improvement of data collection in the industry

Within the paradigm of “Industry 4.0”, data collection and management acquire new relevance. In this context, the introduction of the Internet of Things (IoT) in the manufacturing field allows to develop information systems able to offer the possibility of using a large amount of data collected from heterogeneous sources in real time. The information thus obtained is functional not only to the attainment of an industrial development but also for evaluation and improvement of its sustainability. For example, the benefit obtainable for the life cycle assessment (LCA) methodology from the new digital configuration is represented by a greater specificity of data that wireless sensors networks (WSN) measure and transmit in a continuous way.This paper explores the benefit of using a sensor for the evaluation of the environmental impact, in particular for LCA, in an Italian company producing chemical formulations. The machinery electric consumption directly measured data is compared with the same data estimated with mathematical models. It highlights how much different approach of data measurement and calculation can affect the LCA results. The detection of the energy variable related to a single machine for a particular process, which has been described in the paper, represents a first step towards the implementation of a WSN, proposed by Scatol8 srl, to be used to produce in a more sustainable way.