Multi-criteria analysis for municipal solid waste management in a Brazilian metropolitan area.

The decision-making process involved in municipal solid waste management (MSWM) must consider more than just financial aspects, which makes it a difficult task in developing countries. The Recife Metropolitan Region (RMR) in the Northeast of Brazil faces a MSWM problem that has been ongoing since the 1970s, with no common solution. In order to direct short-term solutions, three MSWM alternatives were outlined for the RMR, considering the current and future situations, the time and cost involved and social/environmental criteria. A multi-criteria approach, based on the Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE), was proposed to rank these alternatives. The alternative that included two private landfill sites and seven transfer, sorting and composting stations was confirmed as the most suitable and stable option for short-term MSWM, considering the two scenarios for the criteria weights. Sensitivity analysis was also performed to support the robustness of the results. The implementation of separate collections would minimize the amount of waste buried, while maximizing the useful life of landfill sites and increasing the timeframe of the alternative. Overall, the multi-criteria analysis was helpful and accurate during the alternative selection process, considering the similarities and restrictions of each option, which can lead to difficulties during the decision-making process.

Microplastics removal efficiency and risk analysis of wastewater treatment plants in Oman.

Microplastics (MPs) have recently been documented as an emerging pollutant that poses a critical threat to environment. Wastewater treatment plants (WWTPs) are commonly regarded as significant contributors to the presence of MPs. This study aimed to assess the MPs load of three wastewater treatment facilities in Oman using various treatments, including MBR, SBR, and CAS. Wastewater samples from influent, effluent, and sludge were collected and analyzed to determine the concentration, morphology, size, color, and polymer type of the MPs. A set of sieves with a mesh size range of 1 mm-45 µm was used to for filtration. Oxidation treatment was applied for all samples using Fenton's reagent, followed by density separation by sodium chloride solution. The Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy (ATR- FTIR) method was utilized to test 10% from each sampling point to confirm the polymer types of the MPs. The pollution load index (PLI) and hazard index (HI) have been employed to assess the risk associated with the chemical toxicity and concentration of detected particles. The PROMETHEE method was used to rank the risk of sampling sites based on different criteria that posed potential ecological and human health risks. The results indicate that the average concentrations of 0.99 MP/L, 1.38 MP/L, and 0.93 MP/L were detected in the final treated effluent of WWTP A, WWTP B, and WWTP C, respectively. These concentrations correspond to overall removal efficiencies of 82.5%, 77.4%, and 79.2% for WWTP A, WWTP B, and WWTP C, respectively Most MPs found in tertiary effluent were smaller particles (425 µm) and fiber-shaped. The major types of MPs were polypropylene (PP), low-density polyethylene (LDPE), polyurethane (PU), polyethylene terephthalate (PET), and Polyvinyl chloride (PVC). This study showed that treated effluent and sludge release significant MPs into the environment.

Evaluating the efficiency of relief centers in disaster and epidemic conditions using multi-criteria decision-making methods and GIS: A case study.

Disaster response refers to any action taken and performed by disaster team managers after and during a disaster. According to the prevalence of the coronavirus and the unpredictability of the behavior of this virus, the capacities of hospitals and medical centers have been overshadowed by this epidemic. Governments have set up temporary rehabilitation centers to control the epidemic, make better use of resources, and quarantine COVID-19 patients. The Tehran (Iran) Disaster Management Organization has designated centers to house the injured and displaced during natural disasters such as floods and earthquakes. In this study, the efficiency and sustainability of the evaluation criteria of selected disaster management centers were evaluated in three scenarios: disaster conditions (natural disasters), epidemic conditions, and disaster-epidemic situations. Firstly, the research criteria were classified by experts using the fuzzy Delphi method and weighted using the triangular fuzzy aggregation method. In addition, the criteria are evaluated as information layers in the Geographic Information System (GIS) and the relief locations determined by the disaster management are evaluated against the research criteria. By forming a decision matrix, the alternatives in all three scenarios were prioritized using the PROMETHEE Method and evaluated in terms of efficiency. As a results, the main ways criterion shown with an impact factor of 13% among the evaluation criteria of centers in disaster situations. Additionally, the security criterion with an impact factor of 22% among the evaluation criteria of centers in epidemic conditions achieved the most important criteria in the PROMETHEE ranking.

Sensitivity Analysis by the PROMETHEE-GAIA method: Algorithms evaluation for COVID-19 prediction.

With the expansion of coronavirus in the World, the search for technology solutions based on the analysis and prospecting of diseases has become constant. The paper addresses a machine learning algorithms analysis used to predict and identify infected patients. For analysis, we use a multicriteria approach using the PROMETHEE-GAIA method, providing the structuring of alternatives respective to a set of criteria, thus enabling the obtaining of their importance degree under the perspective of multiple criteria. The study approaches a sensitivity analysis, evaluating the alternatives using the PROMETHEE I and II methods, along with the GAIA plan, both implemented by the Visual PROMETHEE computational tool, exploring numerical and graphical resources. The analysis model proves to be effective, guaranteeing the ranking of alternatives by inter criterion evaluation and local results with intra criterion evaluation, providing a transparent analysis concerning the selection of prediction algorithms to combat the COVID-19 pandemic.

An integrated approach of PCA and PROMETHEE in spatial assessment of circular economy indicators.

In order to ensure environmental sustainability, reducing the consumption of renewable resources, finding adequate substitutes for non-renewable resources, and reducing the generation of waste and pollution are necessities. The concept of circular economy one of the possible and good responses to improve the sustainability of the system, as it places particular emphasis on the reduction, reutilization and recycling of its elements. The paper presents a comparative analysis of the circular economy development in European Union countries based on the dataset encompasses 11 indicators, covering the seven-year period with biennial data. The analysis was performed using the integrated approach of the Principal Component Analysis and PROMETHEE with the aim of creating a composite index as a measure of the development of the circular economy at the national level. The ranking outcomes indicate that during the observed period Germany has the most developed circular economy, followed by the Netherlands, France and Austria. Additionally, the results of the research clearly indicate the positive correlation between the development of circular economies at the national level and the socio-economic development of the country, while progress in the circular economy has no immediate impact on environmental sustainability, but the effects are realized subsequently, with the intensity of the relationship increasing in two-year lag periods.

Multi-criteria decision analysis and spatial statistic: an approach to determining human vulnerability to vector transmission of Trypanosoma cruzi

BACKGROUND Chagas disease (CD), caused by the protozoan Trypanosoma cruzi, is a neglected human disease. It is endemic to the Americas and is estimated to have an economic impact, including lost productivity and disability, of 7 billion dollars per year on average. OBJECTIVES To assess vulnerability to vector-borne transmission of T. cruzi in domiciliary environments within an area undergoing domiciliary vector interruption of T. cruzi in Colombia. METHODS Multi-criteria decision analysis [preference ranking method for enrichment evaluation (PROMETHEE) and geometrical analysis for interactive assistance (GAIA) methods] and spatial statistics were performed on data from a socio-environmental questionnaire and an entomological survey. In the construction of multi-criteria descriptors, decision-making processes and indicators of five determinants of the CD vector pathway were summarily defined, including: (1) house indicator (HI); (2) triatominae indicator (TI); (3) host/reservoir indicator (Ho/RoI); (4) ecotope indicator (EI); and (5) socio-cultural indicator (S-CI). FINDINGS Determination of vulnerability to CD is mostly influenced by TI, with 44.96% of the total weight in the model, while the lowest contribution was from S-CI, with 7.15%. The five indicators comprise 17 indices, and include 78 of the original 104 priority criteria and variables. The PROMETHEE and GAIA methods proved very efficient for prioritisation and quantitative categorisation of socio-environmental determinants and for better determining which criteria should be considered for interrupting the man-T. cruzi-vector relationship in endemic areas of the Americas. Through the analysis of spatial autocorrelation it is clear that there is a spatial dependence in establishing categories of vulnerability, therefore, the effect of neighbors' setting (border areas) on local values should be incorporated into disease management for establishing programs of surveillance and control of CD via vector. CONCLUSIONS The study model proposed here is flexible and can be adapted to various eco-epidemiological profiles and is suitable for focusing anti-T. cruzi serological surveillance programs in vulnerable human populations.