Exploring tradeoffs among diet quality and environmental impacts in self-selected diets: a population-based study.

PURPOSE: Proposed sustainable diets often deviate dramatically from currently consumed diets, excluding or drastically reducing entire food groups. Moreover, their environmental sustainability tends to be measured only in terms of greenhouse gases emissions. The aim of this study was to overcome these limitations and identify a cluster of already adopted, relatively healthy diets with substantially lower environmental impacts than the average diet. We also aimed to estimate the reduction in multiple environmental impacts that could be achieved by shifting to this diet cluster and highlight possible tradeoffs among environmental impacts. METHODS: The diet clusters were identified by applying energy-adjusted multiple factor analysis and hierarchical clustering to the dietary data of the National FinHealth 2017 Study (n = 5125) harmonized with life cycle assessment data on food products from Agribalyse 3.0 and Agri-Footprint using nutrient intakes and global warming potential, land use, and eutrophication of marine and freshwater systems as the active variables. RESULTS: We identified five diet clusters, none of which had the highest overall diet quality and lowest impact for all four environmental indicators. One cluster, including twenty percent of the individuals in the sample was identified as a "best compromise" diet with the highest diet quality and the second lowest environmental impacts of all clusters, except for freshwater eutrophication. The cluster did not exclude any food groups, but included more fruits, vegetables, and fish and less of all other animal-source foods than average. Shifting to this cluster diet could raise diet quality while achieving significant reductions in most but not all environmental impacts. CONCLUSION: There are tradeoffs among the environmental impacts of diets. Thus, future dietary analyses should consider multiple sustainability indicators simultaneously. Cluster analysis is a useful tool to help design tailored, socio-culturally acceptable dietary transition paths towards high diet quality and lower environmental impact.

A conceptual model to establish preventive and corrective actions to guarantee water safety following scenarios of tailing dam failure.

One of the impacts related to mining dam failures is the change in water quality downstream of the rupture and a knowledge gap is observed in terms of methodologies aimed at the prognosis of impact in water abstractions, a vulnerability that can be identified before a rupture event. Thus, the present work aims to describe a novel methodological proposal, not currently considered by control agencies, of a standard protocol that enables a comprehensive prognosis of the impacts on water quality impact in scenarios of dam failure. Initially, extensive bibliographic research was carried out on the main disruptions events since 1965 intended to better comprehend the impacts on water quality and to identify mitigatory actions proposed by the time. The information provided a framework to propose a conceptual model for the prognosis of water abstractions, with the suggestion of software and studies to comprehend the different scenarios in the event of dam failure. A protocol was prepared to obtain information on potentially affected inhabitants and a multicriteria analysis was developed using the Geographic Information System (GIS) to suggest the employment of preventive and corrective actions. The methodology was demonstrated in the Velhas River basin considering a hypothetical scenario of tailing dam failure. Changes in water quality would be observed in 274 km of its extension, mainly related to alterations in solids, metals, and metalloids' concentration, in addition to the impact on important water treatment plants. The map algebra and the results suggest the need for structuring actions in cases where the water abstraction is intended for human supply and in populations greater than 100,000 inhabitants. Populations smaller than these, or usages other than human supply, could be supplied by water tank trucks or mixed alternatives. The methodology pointed out the necessity for structuring supply actions with due notice, with the potential to prevent water shortages in scenarios of tailing dam failure and to complement the enterprise resource planning of mining companies.

Environmental vulnerability assessment of the Doce River basin, southeastern Brazil.

Environmental vulnerability is an important tool to understand the natural and anthropogenic impacts associated with the susceptibility to environmental damage. This study aims to assess the environmental vulnerability of the Doce River basin in Brazil through Multicriteria Decision Analysis based on Geographic Information Systems (GIS-MCDA). Natural factors (slope, elevation, relief dissection, rainfall, pedology, and geology) and anthropogenic factors (distance from urban centers, roads, mining dams, and land use) were used to determine the environmental vulnerability index (EVI). The EVI was classified into five classes, identifying associated land uses. Vulnerability was verified in water resource management units (UGRHs) and municipalities using hot spot analysis. The study employed the water quality index (WQI) to assess the EVI and global sensitivity analysis (GSA) to evaluate the model input parameters that most influence the basin's environmental vulnerability. The results showed that the regions near the middle Doce River were considered environmentally more vulnerable, especially the UGRHs Guandu, Manhuaçu, and Caratinga; and 35.9% of the basin has high and very high vulnerabilities. Hot spot analysis identified regions with low EVI values (cold spot) in the north and northwest, while areas with high values (hot spot) were concentrated mainly in the middle Doce region. Water monitoring stations with the worst WQI values were found in the most environmentally vulnerable areas. The GSA determined that land use and slope were the primary factors influencing the model's response. The results of this study provide valuable information for supporting environmental planning in the Doce River basin.

A methodological proposal to evaluate the health hazard scenario from COVID-19 in Italy.

2019 Coronavirus disease (COVID-19) had a big impact in Italy, mainly concentrated in the northern part of the Country. All this was mainly due to similarities of this area with Wuhan in Hubei Province, according to geographical, environmental and socio-economic points of view. The basic hypothesis of this research was that the presence of atmospheric pollutants can generate stress on health conditions of the population and determine pre-conditions for the development of diseases of the respiratory system and complications related to them. In most cases the attention on environmental aspects is mainly concentrated on pollution, neglecting issues such as land management which, in some way, can contribute to reducing the impact of pollution. The reduction of land take and the decrease in the loss of ecosystem services can represent an important aspect in improving environmental quality. In order to integrate policies for environmental change and human health, the main factors analyzed in this paper can be summarized in environmental, climatic and land management. The main aim of this paper was to produce three different hazard scenarios respectively related to environmental, climatic and land management-related factors. A Spatial Analytical Hierarchy Process (AHP) method has been applied over thirteen informative layers grouped in aggregation classes of environmental, climatic and land management. The results of the health hazard maps show a disparity in the distribution of territorial responses to the pandemic in Italy. The environmental components play an extremely relevant role in the definition of the red zones of hazard, with a consequent urgent need to renew sustainable development strategies. The comparison of hazard maps related to different scenarios provides decision makers with tools to orient policy choices with a different degree of priority according to a place-based approach. In particular, the geospatial representation of risks could be a tool for legitimizing the measures chosen by decision-makers, proposing a renewed approach that highlights and takes account of the differences between the spatial contexts to be considered - Regions, Provinces, Municipalities - also in terms of climatic and environmental variables.

Incorporating local researchers' and decision makers' preferences for groundwater resources management in a spatial multi-voiced decision model.

Water is a crucial and highly sensitive political issue. The overexploitation of groundwater resources and deterioration of water quality caused by pollution as well as the deficiencies of the existing infrastructure require immediate attention. The main goal of this paper is to carry out a multi-voiced multicriteria analysis that integrates the preferences of local researchers and decision makers in a process aimed at prioritizing watersheds that require the implementation of groundwater management instruments. Using the Criterium Decision Plus system, criteria and subcriteria were integrated into a spatial multi-voiced decision model for the prioritization of watersheds for groundwater resources management. The criteria chosen were Groundwater quality, Groundwater quantity, Land use with potential pollutant load, Equity and Intrinsic aquifer vulnerability. Criteria and subcriteria preferences analysis were derived from workshops with local researchers and decision makers. The spatial multi-voiced decision model identified five of the fourteen watersheds as high to very high priority and requiring groundwater resources management. Based on the local researchers' and decision makers' preferences and hierarchy scheme of the multi-voiced decision model the main criteria and subcriteria that contributed to the final model results were identified. Regarding the criteria, Groundwater quality, Equity and Groundwater quantity contributed extensively to the model. The subcriteria contributions to the groundwater resources management came mainly from High intrinsic aquifer vulnerability, Agrochemicals, Groundwater Storage and Groundwater for domestic supply. This proposed procedure showed that time and effort can be directed to using data and preferences to assist in planning and decision making for groundwater resources management.

Multicriteria analysis on environmental impacts of accelerated vehicle retirement program from a life-cycle perspective: A case study of Beijing.

The environmental benefits of accelerated vehicle retirement programs (AVRPs), which have been extensively adopted in many countries, are highlighted by the proponents. However, the methods for evaluating their environmental effects are lacking of considering material and water criteria as well as continuous improvement in vehicle fuel efficiency and emission control. Additionally, the studies on Chinese case only considered air pollutants during vehicle usage and assumed a fixed remaining lifetime of old vehicles. This study therefore proposed a multicriteria life-cycle analysis model, which embeds not only vehicle lifetime distribution but also dynamics of vehicle fuel efficiency and emission factors, to examine the environmental effects of AVRP more comprehensively in terms of material, water, and energy consumption as well as emission of greenhouse gas, air pollutants and water pollutants. The assessment of the AVRP in Beijing, China, shows that short-term environmental benefits can be hardly gained from a life-cycle perspective, and energy consumption, greenhouse gases and other pollutants (except for volatile organic compound) decrease only when the users keep their new vehicles for 3 years or more. In the medium term, the AVRP would slightly increase material, energy and water consumption, sulfur-oxide, greenhouse gas and water pollutants, but significantly or moderately reduce other air pollutants. Moreover, the results reveal that merely considering the phase of vehicle usage may also lead underestimating some environmental benefits of AVRP by ignoring the phase of fuel production, whilst promoting vehicle fuel efficiency standards and the environmental regulations on vehicle and fuel supply chains may minimize the environmental benefits of AVRP or even have adverse effects.

Multicriteria approach to prioritize forest restoration areas for biodiversity conservation in the eastern Amazon.

Due to the global magnitude of forest degradation and deforestation and the high cost of ecological restoration, several approaches have been used to prioritize conservation or restoration areas based on different objectives and criteria. The present work aims to develop a multicriteria approach to defining forest restoration priority areas in the Itacaiúnas River basin, eastern Amazon, that maximizes the criteria equitably. The selected criteria were: improve forest connectivity, provide climatic refuges for biodiversity, mitigate the impacts of deforestation on streamflow, and improve the probability of natural regeneration. A strong difference between selected areas was observed when the criteria of forest connectivity and mitigate the impact on streamflow were considered separately, but greater equity among the criteria was achieved using the multicriteria approach. The most priority areas were concentrated near protected areas. The method used provides a flexible framework, and different criteria or subarea selections can be applied for different purposes to facilitate adaptive management. Analyzing forest restoration prioritization on rural properties can provide guidance for conserving and restoring biodiversity at the landscape scale while complying with legal requirements.

Analysis of Susceptibility to Degradation of Water Ecosystem Services as a Tool for Land Use Planning: a Case Study in a Small Brazilian Watershed.

Mapping priority areas for environmental conservation and restoration is essential to informing policy formulation and decision-making. This study proposes a methodology based on multicriteria analysis and on-site assessment to develop environmental zoning that enhances the provision of water ecosystem services (WES) from Brazil's Água Quente River Basin. Integrated analysis of multiple criteria enabled identification of degrees of susceptibility to degradation, assessment of effects of land-use changes between 1990 and 2020, and validation of the study's methodology via field protocol. The results indicated that the spatial and temporal patterns of WES susceptibility to degradation varied little within the study area with the most critical levels occurring primarily in the Agua Quente's floodplain, where there are sandy textured soils and coverage with a low degree of soil protection. Zoning analysis designates 40% of the basin`s area as consolidated use, 28% for environmental conservation, 19% as anthropic use, and 13% for environmental restoration. Field analysis indicates that the occurrence of degraded areas and pollution by solid waste and urban effluents are relevant factors that affect the basin's water resources. Linear regression analysis indicated a good fit between the data modeled by the multicriteria analysis and those observed on-site (R² = 0.6 p < 0.05). The study's method is effective and its structure can be used in other river basins, as its approach is simple and flexible and can be readily adjusted to fit the characteristics of the study site.

A new measure of treatment effect in clinical trials involving competing risks based on generalized pairwise comparisons.

In survival analysis with competing risks, the treatment effect is typically expressed using cause-specific or subdistribution hazard ratios, both relying on proportional hazards assumptions. This paper proposes a nonparametric approach to analyze competing risks data based on generalized pairwise comparisons (GPC). GPC estimate the net benefit, defined as the probability that a patient from the treatment group has a better outcome than a patient from the control group minus the probability of the opposite situation, by comparing all pairs of patients taking one patient from each group. GPC allow using clinically relevant thresholds and simultaneously analyzing multiple prioritized endpoints. We show that under proportional subdistribution hazards, the net benefit for competing risks settings can be expressed as a decreasing function of the subdistribution hazard ratio, taking a value 0 when the latter equals 1. We propose four net benefit estimators dealing differently with censoring. Among them, the Péron estimator uses the Aalen-Johansen estimator of the cumulative incidence functions to classify the pairs for which the patient with the best outcome could not be determined due to censoring. We use simulations to study the bias of these estimators and the size and power of the tests based on the net benefit. The Péron estimator was approximately unbiased when the sample size was large and the censoring distribution's support sufficiently wide. With one endpoint, our approach showed a comparable power to a proportional subdistribution hazards model even under proportional subdistribution hazards. An application of the methodology in oncology is provided.

An Integrated Framework for Environmental Multi-Impact Spatial Risk Analysis.

Quantitative risk analysis is being extensively employed to support policymakers and provides a strong conceptual framework for evaluating decision alternatives under uncertainty. Many problems involving environmental risks are, however, of a spatial nature, i.e., containing spatial impacts, spatial vulnerabilities, and spatial risk-mitigation alternatives. Recent developments in multicriteria spatial analysis have enabled the assessment and aggregation of multiple impacts, supporting policymakers in spatial evaluation problems. However, recent attempts to conduct spatial multicriteria risk analysis have generally been weakly conceptualized, without adequate roots in quantitative risk analysis. Moreover, assessments of spatial risk often neglect the multidimensional nature of spatial impacts (e.g., social, economic, human) that are typically occurring in such decision problems. The aim of this article is therefore to suggest a conceptual quantitative framework for environmental multicriteria spatial risk analysis based on expected multi-attribute utility theory. The framework proposes: (i) the formal assessment of multiple spatial impacts; (ii) the aggregation of these multiple spatial impacts; (iii) the assessment of spatial vulnerabilities and probabilities of occurrence of adverse events; (iv) the computation of spatial risks; (v) the assessment of spatial risk mitigation alternatives; and (vi) the design and comparison of spatial risk mitigation alternatives (e.g., reductions of vulnerabilities and/or impacts). We illustrate the use of the framework in practice with a case study based on a flood-prone area in northern Italy.

A simplified approach to determine the carbon footprint of a region: Key learning points from a Galician study.

On a previous study, the carbon footprint (CF) of all production and consumption activities of Galicia, an Autonomous Community located in the north-west of Spain, was determined and the results were used to devise strategies aimed at the reduction and mitigation of the greenhouse gas (GHG) emissions. The territorial LCA methodology was used there to perform the calculations. However, that methodology was initially designed to compute the emissions of all types of polluting substances to the environment (several thousands of substances considered in the life cycle inventories), aimed at performing complete LCA studies. This requirement implies the use of specific modelling approaches and databases that in turn raised some difficulties, i.e., need of large amounts of data (which increased gathering times), low temporal, geographical and technological representativeness of the study, lack of data, and presence of double counting issues when trying to combine the sectorial CF results into those of the total economy. In view of these of difficulties, and considering the need to focus only on GHG emissions, it seems important to improve the robustness of the CF computation while proposing a simplified methodology. This study is the result of those efforts to improve the aforementioned methodology. In addition to the territorial LCA approach, several Input-Output (IO) based alternatives have been used here to compute direct and indirect GHG emissions of all Galician production and consumption activities. The results of the different alternatives were compared and evaluated under a multi-criteria approach considering reliability, completeness, temporal and geographical correlation, applicability and consistency. Based on that, an improved and simplified methodology was proposed to determine the CF of the Galician consumption and production activities from a total responsibility perspective. This methodology adequately reflects the current characteristics of the Galician economy, thus increasing the representativeness of the results, and can be applied to any region in which IO tables and environmental vectors are available. This methodology could thus provide useful information in decision making processes to reduce and prevent GHG emissions.

Using Multicriteria Approaches to Assess the Value of Health Care.

Practitioners of cost-utility analysis know that their models omit several important factors that often affect real-world decisions about health care options. Furthermore, cost-utility analyses typically reflect only single perspectives (e.g., individual, business, and societal), further limiting the value for those with different perspectives (patients, providers, payers, producers, and planners-the 5Ps). We discuss how models based on multicriteria analyses, which look at problems from many perspectives, can fill this void. Each of the 5Ps can use multicriteria analyses in different ways to aid their decisions. Each perspective may lead to different value measures and outcomes, whereas no single-metric approach (such as cost-utility analysis) can satisfy all these stakeholders. All stakeholders have unique ways to measure value, even if assessing the same health intervention. We illustrate the benefits of this approach by comparing the value of five different hypothetical treatment choices for five hypothetical patients with cancer, each with different preference structures. Nine attributes describe each treatment option. We add a brief discussion regarding the use of these approaches in group-based decisions. We urge that methods to value health interventions embrace the multicriteria approaches that we discuss, because these approaches 1) increase transparency about the decision process, 2) allow flight simulator-type evaluation of alternative interventions before actual investment or deployment, 3) help focus efforts to improve data in an efficient manner, 4) at least in some cases help facilitate decision convergence among stakeholders with differing perspectives, and 5) help avoid potential cognitive errors known to impair intuitive judgments.

Restoration planning to guide Aichi targets in a megadiverse country.

Ecological restoration has become an important strategy to conserve biodiversity and ecosystems services. To restore 15% of degraded ecosystems as stipulated by the Convention on Biological Diversity Aichi target 15, we developed a prioritization framework to identify potential priority sites for restoration in Mexico, a megadiverse country. We used the most current biological and environmental data on Mexico to assess areas of biological importance and restoration feasibility at national scale and engaged stakeholders and experts throughout the process. We integrated 8 criteria into 2 components (i.e., biological importance and restoration feasibility) in a spatial multicriteria analysis and generated 11 scenarios to test the effect of assigning different component weights. The priority restoration sites were distributed across all terrestrial ecosystems of Mexico; 64.1% were in degraded natural vegetation and 6% were in protected areas. Our results provide a spatial guide to where restoration could enhance the persistence of species of conservation concern and vulnerable ecosystems while maximizing the likelihood of restoration success. Such spatial prioritization is a first step in informing policy makers and restoration planners where to focus local and large-scale restoration efforts, which should additionally incorporate social and monetary cost-benefit considerations.

Use of multicriteria analysis (MCA) for sustainable hydropower planning and management.

Multicriteria analysis (MCA) is a decision-making tool applied to a wide range of environmental management problems, including renewable energy planning and management. An interesting field of application of MCA is the evaluation and analysis of the conflicting aspects of hydropower (HP) exploitation, affecting the three pillars of sustainability and involving several different stakeholders. The present study was aimed at reviewing the state of the art of MCA applications to sustainable hydropower production and related decision-making problems, based on a detailed analysis of the scientific papers published over the last 15 years on this topic. The papers were analysed and compared, focusing on the specific features of the MCA methods applied in the described case studies, highlighting the general aspects of the MCA application (purpose, spatial scale, software used, stakeholders, etc.) and the specific operational/technical features of the selected MCA technique (methodology, criteria, evaluation, approach, sensitivity, etc.). Some specific limitations of the analysed case studies were identified and a set of "quality indexes" of an exhaustive MCA application were suggested as potential improvements for more effectively support decision-making processes in sustainable HP planning and management problems.

A multicriteria decision making approach applied to improving maintenance policies in healthcare organizations.

BACKGROUND: Healthcare organizations have far greater maintenance needs for their medical equipment than other organization, as many are used directly with patients. However, the literature on asset management in healthcare organizations is very limited. The aim of this research is to provide more rational application of maintenance policies, leading to an increase in quality of care. METHODS: This article describes a multicriteria decision-making approach which integrates Markov chains with the multicriteria Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH), to facilitate the best choice of combination of maintenance policies by using the judgements of a multi-disciplinary decision group. The proposed approach takes into account the level of acceptance that a given alternative would have among professionals. It also takes into account criteria related to cost, quality of care and impact of care cover. RESULTS: This multicriteria approach is applied to four dialysis subsystems: patients infected with hepatitis C, infected with hepatitis B, acute and chronic; in all cases, the maintenance strategy obtained consists of applying corrective and preventive maintenance plus two reserve machines. CONCLUSIONS: The added value in decision-making practices from this research comes from: (i) integrating the use of Markov chains to obtain the alternatives to be assessed by a multicriteria methodology; (ii) proposing the use of MACBETH to make rational decisions on asset management in healthcare organizations; (iii) applying the multicriteria approach to select a set or combination of maintenance policies in four dialysis subsystems of a health care organization. In the multicriteria decision making approach proposed, economic criteria have been used, related to the quality of care which is desired for patients (availability), and the acceptance that each alternative would have considering the maintenance and healthcare resources which exist in the organization, with the inclusion of a decision-making group. This approach is better suited to actual health care organization practice and depending on the subsystem analysed, improvements are introduced that are not included in normal maintenance policies; in this way, not only have different maintenance policies been suggested, but also alternatives that, in each case and according to viability, provide a more complete decision tool for the maintenance manager.

Risk-cost-benefit analysis for transportation corridors with interval uncertainties of heterogeneous data.

Access management, which systematically limits opportunities for egress and ingress of vehicles to highway lanes, is critical to protect trillions of dollars of current investment in transportation. This article addresses allocating resources for access management with incomplete and partially relevant data on crash rates, travel speeds, and other factors. While access management can be effective to avoid crashes, reduce travel times, and increase route capacities, the literature suggests a need for performance metrics to guide investments in resource allocation across large corridor networks and several time horizons. In this article, we describe a quantitative decision model to support an access management program via risk-cost-benefit analysis under data uncertainties from diverse sources of data and expertise. The approach quantifies potential benefits, including safety improvement and travel time savings, and costs of access management through functional relationships of input parameters including crash rates, corridor access point densities, and traffic volumes. Parameter uncertainties, which vary across locales and experts, are addressed via numerical interval analyses. This approach is demonstrated at several geographic scales across 7,000 kilometers of highways in a geographic region and several subregions. The demonstration prioritizes route segments that would benefit from risk management, including (i) additional data or elicitation, (ii) right-of-way purchases, (iii) restriction or closing of access points, (iv) new alignments, (v) developer proffers, and (vi) etc. The approach ought to be of wide interest to analysts, planners, policymakers, and stakeholders who rely on heterogeneous data and expertise for risk management.

Integrating groundwater into land planning: a risk assessment methodology.

Generally, groundwater is naturally of good quality for human consumption and represents an essential source of drinking water. In Canada, small municipalities and individuals are particularly reliant on groundwater, since they cannot afford complex water treatment installations. However, groundwater is a vulnerable resource that, depending on its characteristics, can be contaminated by almost any land use. In recent decades, governments have launched programs to acquire more information on groundwater, in order to better protect it. Nevertheless, the data produced are rarely adequate to be understood and used by land planners. The aim of this study was to develop a method that helps planners interpret hydrogeological data in the Province of Quebec, Canada. Based on the requests and needs of planners during semi-directed interviews, a methodology was developed to qualitatively evaluate groundwater contamination risk by land uses. The method combines land planning data and hydrogeological data through the MACBETH multicriteria analysis method, to obtain maps of groundwater contamination risk. The method was developed through group and individual meetings with numerous hydrogeology, land planning, water's economics and drinking water specialists. The resulting maps allow planners to understand the dynamics of groundwater within their territory, identify problem areas where groundwater is threatened and analyse the potential impact of planning scenarios on the risk of groundwater contamination.

Decision support systems for environmental management: a case study on wastewater from agriculture.

Dealing with spatial decision problems means combining and transforming geographical data (input) into a resultant decision (output), interfacing a Geographical Information System (GIS) with Multi-Criteria Decision Analysis (MCDA) methods. The conventional MCDA approach assumes the spatial homogeneity of alternatives within the case study area, although it is often unrealistic. On the other side, GIS provides excellent data acquisition, storage, manipulation and analysis capabilities, but in the case of a value structure analysis this capability is lower. For these reasons, several studies in the last twenty years have given attention to MCDA-GIS integration and to the development of Spatial Decision Support Systems (SDSS). Hitherto, most of these applications are based only on a formal integration between the two approaches. In this paper, we propose a complete MCDA-GIS integration with a plurality of MCDA methodologies, grouped in a suite. More precisely, we considered an open-source GIS (GRASS GIS 6.4) and a modular package including five MCDA modules based on five different methodologies. The methods included are: ELECTRE I, Fuzzy set, REGIME analysis, Analytic Hierarchy Process and Dominance-based Rough Set Approach. Thanks to the modular nature of the package, it is possible to add new methods without modifying the existing structure. To present the suite, we applied each module to the same case study, making comparisons. The strong points of the MCDA-GIS integration we developed are its open-source setting and the user friendly interface, both thanks to GRASS GIS, and the use of raster data. Moreover, our suite is a genuine case of perfect integration, where the spatial nature of criteria is always present.

GIS-based multicriteria municipal solid waste landfill suitability analysis: a review of the methodologies performed and criteria implemented.

Multicriteria spatial decision support systems (MC-SDSS) have emerged as an integration of the geographical information systems (GIS) and multiple criteria decision analysis (MCDA) methods. GIS-based MCDA allows the incorporation of conflicting objectives and decision maker (DM) preferences into spatial decision models. During recent decades, a variety of research articles have been published regarding the implementation of methods and/or tools in a variety of real-world case studies. The article discusses, in detail, the criteria and methods that are implemented in GIS-based landfill siting suitability analysis and especially the exclusionary and non-exclusionary criteria that can be considered when selecting sites for municipal solid waste (MSW) landfills. This paper reviews 36 seminal articles in which the evaluation of candidate landfill sites is conducted using MCDA methods. After a brief description of the main components of a MC-SDSS and the applied decision rules, the review focuses on the criteria incorporated into the decision models. The review provides a comprehensive guide to the landfill siting analysis criteria, providing details regarding the utilization methods, their decision or exclusionary nature and their monotonicity.

Occurrence, spatiotemporal trends, fate, and treatment technologies for microplastics and organic contaminants in biosolids: A review.

This review provides a comprehensive overview of the occurrence, fate, treatment and multi-criteria analysis of microplastics (MPs) and organic contaminants (OCs) in biosolids. A meta-analysis was complementarily analysed through the literature to map out the occurrence and fate of MPs and 10 different groups of OCs. The data demonstrate that MPs (54.7% occurrence rate) and linear alkylbenzene sulfonate surfactants (44.2% occurrence rate) account for the highest prevalence of contaminants in biosolids. In turn, dioxin, polychlorinated biphenyls (PCBs) and phosphorus flame retardants (PFRs) have the lowest rates (<0.01%). The occurrence of several OCs (e.g., dioxin, per- and polyfluoroalkyl substances, polycyclic aromatic hydrocarbons, pharmaceutical and personal care products, ultraviolet filters, phosphate flame retardants) in Europe appear at higher rates than in Asia and the Americas. However, MP concentrations in biosolids from Australia are reported to be 10 times higher than in America and Europe, which required more measurement data for in-depth analysis. Amongst the OC groups, brominated flame retardants exhibited exceptional sorption to biosolids with partitioning coefficients (log Kd) higher than 4. To remove these contaminants from biosolids, a wide range of technologies have been developed. Our multicriteria analysis shows that anaerobic digestion is the most mature and practical. Thermal treatment is a viable option; however, it still requires additional improvements in infrastructure, legislation, and public acceptance.