Estimation of lithium-ion battery scrap generation from electric vehicles in Brazil.

Among the diversity of electronic waste, lithium-ion batteries (LIB), specifically those used in the propulsion of electric vehicles (EV), are considered pollutants of significant impact. When not used and disposed of correctly, LIBs can cause damage of various types to health and the environment. The electrochemical instability inherent in these batteries releases toxic gases, risks explosion, and is always associated with a series of electronic circuits composed of various metals, including heavy metals. As a result of public policies to encourage vehicle electrification, the Brazilian EVs sector has shown high growth, even within an economic crisis scenario. In this sense, this study presents a model for estimating the production of electric vehicles and the generation of scrap LIBs, based on time series, combining battery life, car sales data, and the mileage profile covered by a car in Brazil. Around 700 thousand EVs are expected to be circulating in Brazil by 2030, with approximately 500 thousand LIBs to be converted into scrap by 2040. Finally, the delaying effect of the scrap generated from LIBs is highlighted, in line with the battery life, which, in the future, may have a very negative impact on waste management.

A forecasting model based on ARIMA and artificial neural networks for end-OF-life vehicles.

The accelerated growth of the automotive supply network has had an immeasurable impact on the environment, especially relating to reusing and disposal of materials. The appropriate management of End-of-Life Vehicles (ELV) has become an imperative item for achieving sustainable development in the field of interest and it is, therefore, a target of special attention from global economies in recent years. Therefore, the present study aims to estimate the future generation of ELVs to assist decision making and mitigate the global impact of this type of waste on the environment. For this, a hybrid forecasting model was used, based on Autoregressive Integrated Moving Average (ARIMA) methodology and on Artificial Neural Networks (ANN), with a set of temporal data extracted from Brazilian sectoral platforms. The results achieved point to a good convergence of the model, indicating better performance than a naive or trivial prediction. The efficiency obtained by the Nash-Sutcliffe coefficient was 98% and the expectation is that for the year 2030, approximately 5.2 million ELVs will be produced in Brazil, of which only 78 thousand units would be effectively recycled, considering the current vehicle recycling rate in the country. Considering the scarcity of information that supports decision-making in waste management in Brazil, this study may also contribute to the proposition of alternatives that favor the proper management of automotive waste, providing a reference for the formulation and implementation of policies related to ELVs in the country.

Fuzzy Cognitive Scenario Mapping for Causes of Cybersecurity in Telehealth Services.

Hospital organizations have adopted telehealth systems to expand their services to a portion of the Brazilian population with limited access to healthcare, mainly due to the geographical distance between their communities and hospitals. The importance and usage of those services have recently increased due to the COVID-19 state-level mobility interventions. These services work with sensitive and confidential data that contain medical records, medication prescriptions, and results of diagnostic processes. Understanding how cybersecurity impacts the development of telehealth strategies is crucial for creating secure systems for daily operations. In the application reported in this article, the Fuzzy Cognitive Maps (FCMs) translated the complexity of cybersecurity in telehealth services into intelligible and objective results in an expert-based cognitive map. The tool also allowed the construction of scenarios simulating the possible implications caused by common factors that affect telehealth systems. FCMs provide a better understanding of cybersecurity strategies using expert knowledge and scenario analysis, enabling the maturation of cybersecurity in telehealth services.

A Risk Assessment Framework Proposal Based on Bow-Tie Analysis for Medical Image Diagnosis Sharing within Telemedicine.

The purpose of this paper is to propose a framework for cybersecurity risk management in telemedicine. The framework, which uses a bow-tie approach for medical image diagnosis sharing, allows the identification, analysis, and assessment of risks, considering the ISO/TS 13131:2014 recommendations. The bow-tie method combines fault tree analysis (FTA) and event tree analysis (ETA). The literature review supported the identification of the main causes and forms of control associated with cybersecurity risks in telemedicine. The main finding of this paper is that it is possible, through a structured model, to manage risks and avoid losses for everyone involved in the process of exchanging medical image information through telemedicine services. Through the framework, those responsible for the telemedicine services can identify potential risks in cybersecurity and act preventively, recognizing the causes even as, in a mitigating way, identifying viable controls and prioritizing investments. Despite the existence of many studies on cybersecurity, the paper provides theoretical contributions to studies on cybersecurity risks and features a new methodological approach, which incorporates both causes and consequences of the incident scenario.

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.

Generation of domestic waste electrical and electronic equipment on Fernando de Noronha Island: qualitative and quantitative aspects.

The accelerated growth trajectory of waste electrical and electronic equipment (WEEE) is a matter of concern for governments worldwide. In developing countries, the problem is more complex because municipal waste management is still a challenge for municipalities. Fernando de Noronha Island, an environmentally protected area, has a transfer station for solid waste before it is sent to the final destination abroad, which is different waste management model to most urban areas. In order to check the specifics of management of WEEE, this study aimed to qualitatively and quantitatively evaluate the generation of this type of waste on the main island of Fernando de Noronha, taking into consideration aspects related to consumption habits and handling of waste. During the in situ research, a questionnaire was applied to a sample of 83 households. The results provide a picture of the generation of WEEE for a period of 1 year, when a production of 1.3 tons of WEEE was estimated. Relationships between education level and monthly income and between education level and number of plasma/LCD TVs and washing machines were confirmed. Another important result is that only two socioeconomic variables (monthly income and education level) are related to two recycling behavior variables. In addition, the population and government treat WEEE as ordinary waste, ignoring its contaminant potential. Despite the existence of relevant legislation concerning the treatment and disposal of WEEE, additional efforts will be required by the government in order to properly manage this type of waste on the island.