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- ItemAssessment of the economic and social impacts of new technologies regarding collection and transportation of recyclable waste in smart cities(Universidade Federal do Espírito Santo, 2025-09-29) Menezes, Hendrigo Noetzold Venes; Rosa, Rodrigo de Alvarenga; https://orcid.org/0000-0003-0841-514X; http://lattes.cnpq.br/7706827408886021; https://orcid.org/0000-0001-7839-6525; http://lattes.cnpq.br/7619979378499321; Buarque, Diogo Costa; https://orcid.org/0000-0003-2698-520X; http://lattes.cnpq.br/8616432679482558; Gama, João Luiz Calmon Nogueira da; https://orcid.org/0000-0002-3054-4784; http://lattes.cnpq.br/7619015734946549; Bovea-Edo, María-Dolores; https://orcid.org/0000-0002-8261-8693; http://lattes.cnpq.br/8964676546513844; Forés, Valeria Ibáñez; https://orcid.org/0000-0001-9047-0097; http://lattes.cnpq.br/1111665377225535The objective of this thesis is to assess the economic and social impacts of implementing new technologies for the collection and transportation of recyclable Municipal Solid Waste (MSW) in the context of Smart Cities (SCs), especially in low/middle-income countries. The research is composed of three interconnected articles. The first one presents a systematic and bibliometric literature review, which revealed that most international scientific output in the field prioritizes environmental efficiency and cost reduction. Social aspects, such as the inclusion of vulnerable communities or labor rights of informal waste pickers, are largely underrepresented. This suggests a significant imbalance in how MSW management is approached in smart city discussions. The second chapter addresses this gap by proposing and applying a route optimization model in the municipality of Aracruz, Brazil. Using Vehicle Routing Problem (VRP) and Simulated Annealing (SA) metaheuristic, the model simulates multiple vehicle trips and scenarios that include Indigenous communities historically excluded from public waste collection services. The results show that it is possible to reach all districts, urban and rural, without increasing operational costs. This reinforces the potential of data-driven tools in supporting more equitable and efficient MSW systems, provided they are informed by local context and planning sensitivity. The third chapter expands the discussion by proposing a set of social performance indicators for evaluating MSW systems based on the Social Life Cycle Assessment (S-LCA) methodology. These indicators were adapted to realities commonly found in low/middle-income countries and tested in the same case study. The analysis revealed structural social vulnerabilities in MSW management, such as lack of social protection for waste workers, poor stakeholder participation, and gender related disparities. In summary, the integration of route optimization models and social performance indicators provides a more comprehensive decision-support framework for municipalities aiming to implement inclusive smart waste strategies. Rather than focusing solely on cost or efficiency, MSW systems must also address social equity and institutional resilience as central pillars for sustainable urban development.
- ItemM-quantile estimation and discriminant analysis for heteroscedastic processes(Universidade Federal do Espírito Santo, 2025-07-09) Patrocinio, Patrick Ferreira; Bondon, Pascal Thierry; https://orcid.org/0000-0002-5158-7337; Reisen, Valdério Anselmo ; https://orcid.org/0000-0002-8313-7648; http://lattes.cnpq.br/9401938646002189; https://orcid.org/0000-0002-8541-2447; http://lattes.cnpq.br/2444124730316324; Goulart, Elisa Valentim ; https://orcid.org/0000-0002-0051-0778; http://lattes.cnpq.br/0014236670973457; Silva, Maria Eduarda ; https://orcid.org/0000-0003-2972-2050; Leskow, Jacek; https://orcid.org/0000-0003-2228-393X; http://lattes.cnpq.br/9225337383254363; Morettin, Pedro Alberto; https://orcid.org/0000-0002-8611-867X; http://lattes.cnpq.br/1532548827466292; Wu, Wei Biao; https://orcid.org/0000-0003-4310-9965; http://lattes.cnpq.br/2092444731656924Based on techniques in the time and frequency domains, this work introduces the M-quantile estimator, which combines the well-known quantile and M-regression functions to address model estimation and discriminant problems, such as classification and dimensionality reduction, in the context of time series with short- and long-memory properties and conditional variance (heteroscedasticity). These phenomena are quite common in real-world problems across many scientific fields, particularly in air quality studies, which motivate this work's main contributions from theoretical and applied perspectives. This thesis is divided into three chapters, and the main contributions are as follows: Chapter 2 explores the M-quantile estimator from a time-domain perspective by introducing the M-quantile Huber loss function to minimise process estimation errors. This approach is an alternative estimation method for time series data, offering advantages over standard estimation methods, such as the conditional least squares estimator, which can be seen as a special case of the proposed approach. Some theoretical issues are discussed, and simulations and applications are provided to support its use in real-world problems. The second and third main contributions are presented in Chapters 3 and 4, respectively. These chapters propose the M-quantile periodogram as an estimator of the spectral function to be used in a discriminant technique constructed based on the cepstral function for short- and long-memory processes with heteroscedastic errors. The asymptotic properties of the M-quantile cepstral discriminant functions are derived. Since the proposed approaches, including the M-quantile periodogram, are relatively novel in the literature, the asymptotic properties of certain sample quantities have been left for future research. Simulations were conducted to evaluate the performance of the M-quantile discriminant function in finite sample sizes. The results reveal interesting findings, particularly regarding the superiority of the M-quantile discriminant function over the cepstral periodogram-based discriminant function for both short- and long-memory processes, with and without additive outliers and non-Gaussian distributions. To demonstrate the usefulness of the proposed methodology in real-world applications, large datasets of PM_10 and PM_2.5 pollutant measurements from more than 200 air quality monitoring stations in France were analysed. The empirical evidence showed promising source classification results in both cases, strongly supporting the use of the M-quantile cepstral sample function in real-world applications such as classification, dimensionality reduction, and cointegration, among others
- ItemVigilância ambiental de Sars-cov-2 em matrizes ambientais na região da Grande Vitória – ES(Universidade Federal do Espírito Santo, 2025-02-21) Costa, Gizely Azevedo; Cassini, Sérvio Túlio Alves; Keller, Regina de Pinho; http://lattes.cnpq.br/1765455668560897; Kaminador, Diogo Costa Buarque; Damasceno, Daniele; Sato, Maria Inês Zanoli; Razzolini, Maria Tereza PepeThe discovery of the new coronavirus SARS-CoV-2, the etiological agent of COVID-19 marked the year 2020. The rapid spread of the SARS-CoV-2 virus led to the declaration by the World Health Organization (WHO) of the COVID-19 pandemic on March 11, 2020. The world faced one of the greatest public health challenges due to the high transmission rate of the SARS-CoV-2 virus and the large number of asymptomatic individuals transmitting the virus. Due to mild or no symptoms, many asymptomatic individuals were not included in traditional clinical data, which led to underreporting of cases and made it difficult to assess the true spread of COVID-19. SARS-CoV-2 was identified in environmental matrices, including sewage, which allowed the adoption of complementary strategies for monitoring the spread of SARS-CoV-2, making the use of complementary tools such as downstream wastewater-based epidemiology (WBE), and a viable alternative capable of predicting early outbreaks and providing reliable data. This study aimed to analyze the presence of SARS-CoV-2 viral RNA in environmental samples of raw sewage and sludge, correlating viral load data (CG/L) with cases of COVID-19 reported by the health department in the Greater Vitória region - ES, Brazil. The study methodology consisted of collecting sewage and sludge samples from different locations: group (a) sewage treatment plants (STPs) and three urban surface channels, between January 2021 and February 2022, and group (b) sludge from an upflow anaerobic reactor (UASB) at ETE Araçás, in Vila Velha/ES, between October 2023 and August 2024. To detect viral RNA, the concentration method proposed by Katayama et al. (2002) was used, followed by RNA extraction and RT-qPCR. The results demonstrated high positivity in the detection of SARS-CoV-2 in all matrices: 87.2% (75/86) in urban channels, 85.3% (70/82) in STPs and 80% in UASB sludge samples. Viral RNA concentrations ranged from 1.59 x 10⁴ to 2.56 x 10⁴ GC/L in urban channels and from 7.79 x 10³ to 1.26 x 10⁴ GC/L in STPs. A moderate to strong correlation was identified between viral load and confirmed cases of COVID-19 in the populations served by the canal basin and STPs monitored in Greater Vitória/ES, with the highest values found in urban channels (Channel 1: r = 0.58; Channel 2: r = 0.78; Channel 3: r = 0.86). This study was one of the pioneers in establishing the presence of the SARS-CoV-2 virus in different matrices, raw sewage and sludge, in the Greater Vitória/ES region. Urban surface channels showed higher viral concentration and better correlation with epidemiological data compared to STPs, standing out as alternative and viable points for monitoring SARS-CoV-2, especially in regions with poor sanitation. Additionally, the high detection of viral RNA in sludge reaffirms its potential as a complementary tool in tracking viral spread in wastewater treatment environments.
- ItemÍndice de segurança do abastecimento de água para comunidades rurais(Universidade Federal do Espírito Santo, 2024-12-18) Trindade, Priscilla Basilio Cardoso Barros; Coelho, Edumar Ramos Cabral; https://orcid.org/0000-0002-9220-5737; Reis, José Antônio Tosta dos; Keller, Regina Pinho; Oliveira, Mariângela Dutra de; Machado, Anna Virgínia MunizRural areas receive less investment in sanitation than urban areas, and there is also a lack of monitoring, maintenance, training, and management in these regions. The ability to summarize indexes facilitates communication among users and is therefore an important tool in planning, management, and decision-making processes. This study developed the Rural Water Supply Security Index (ISAAR) with the help of a literature review and consultation with experts in the field using the Delphi method. The objective of ISAAR is to assist managers and decision-makers in assessing water security in rural areas, considering dimensions that include the watershed, health, sewage, solid waste, water quality, frequency of water supply, and management. ISAAR was applied to rural communities in Espírito Santo, Piauí, and Ceará, in addition to simulations of hypothetical scenarios to verify the behavior of the index. The results reflected the reality of the communities analyzed, and the simulations allowed us to verify that the dimensions and their weights were adequate in the index. ISAAR can be used as a tool to assess the safety of treated water in rural communities and also to demonstrate and synthesize assessments to identify factors that have potential for improvement considering the seven dimensions that comprise it.
- ItemRastreamento e prevalência de salmonella sp. na cadeia produtiva da pimenta-do-reino (piper nigrum) no Espírito Santo(Universidade Federal do Espírito Santo, 2024-09-20) Vinha, Mariana Barboza; Nascimento, Maristela da Silva do; https://orcid.org/0000-0003-1791-0361; Cassini, Sérvio Túlio Alves; https://orcid.org/0000-0001-5200-3666; https://orcid.org/0009-0002-3314-7896; Keller, Regina de Pinho; Silveira, Daniele Damasceno; Oliveira, Jairo Pinto de; Ventura, José AiresContamination of black pepper with Salmonella is a frequent problem in retail and imported shipments. However, there is scarce information about the prevalence of the pathogen in the initial stages of black pepper production chain. This study sought to bridge this gap in research by determining the prevalence, as well as quantifying, and identifying the main Salmonella serovars present during black pepper primary production and processing. Black pepper (233) and environmental (175) samples were collected from farms (354) and processing plants (54) in Espírito Santo, Brazil. The pathogen was detected in soil (16.7%), drying waste (20.4%), fallen berries (3.7%), threshed berries (14.3%), and dried peppercorns (22.2%) collected from farms. Salmonella was also detected in samples of raw material (11.1%), export products (16.7%), and processing waste (16.7%) collected from processing plants. A total of 12 serotypes were identified, and Salmonella Javiana showed the highest prevalence (38.8%). According to the results, contaminations can occur during black pepper harvest and post-harvest, increase or persist throughout post-harvest and remain in the grains produced on rural properties. The processing performed by exporting companies did not eliminate or reduce these contaminations to a safe level, resulting in contamination of the product intended for export The presence of the pathogen in the environment increases the risk of contamination of the fruits and pepper grains during processing. However, this risk can be reduced by improving hygiene practices during processing and by adopting Good Agricultural Practices (GAP) and Good Manufacturing Practices (GMP). To ensure product safety, it is essential to prevent contaminations and to make changes to the current production process, including the implementation of treatments that reduce and control contamination. Public policies aimed at improving rural sanitation, promoting the adoption of GAP, and advancing processing technologies are crucial for driving the necessary changes that will ensure the safety of black pepper produced in Espírito Santo.