Treatment of wastewater containing pharmaceutical compounds by catalytic wet peroxide oxidation using clay-based materials as catalysts

Dupla diplomação UTFPRThis work deals with the treatment of wastewater containing paracetamol, used as a model pharmaceutical emergent pollutant, by catalytic wet peroxide oxidation using clay-based materials as catalysts. The catalysts prepared in this work were clays activated through acid treatment and clays pillared with Co and Fe. For the preparation, natural clays from four different regions of Kazakhstan were used: Akzhar, Asa, Karatau and Kokshetau. The FTIR analysis showed that the pillared clays have a higher amount of iron in its structure when compared with the natural materials, suggesting that the intercalation of iron was successful. The N2 adsorption isotherms obtained were classified as Type II, typical of macroporous materials. The acid characterization showed that the procedures used for the preparation of the acid activated clays and of the pillared clays caused structural modifications. After the preparation and characterization, the pillared materials were tested in the degradation of paracetamol by catalytic wet peroxide oxidation (CWPO). Paracetamol concentration, hydrogen peroxide concentration and total organic carbon analysis (TOC) were followed against time. The material with the best activity was the Kokshetau pillared clay (KOP), with a complete conversion of the pollutant being obtained between 240 and 360 minutes of reaction, followed by a negligible iron leaching of 0.011 %. This leaching left the reaction system with a concentration of 0.089 mg/L of Fe, which is lower than the limit established by the European legislation for discharge in natural water courses (2 mg/L). Since the Kokshetau pillared clay presented the best result, other Kokshetau-based samples (activated, calcined and natural) were also tested in the CWPO of paracetamol. The higher efficiency of KOP in the CWPO of paracetamol can be explained by the fact that this material has a higher acidity, basicity and surface area when compared to the other pillared samples.Este trabalho aborda o tratamento de águas residuais que contém paracetamol, como poluente emergente modelo, por oxidação humida com peróxido de hidrogênio usando argilas como catalisadores. Os catalisadores a base de argila preparados neste trabalho foram as argilas ativadas mediante tratamento com ácido e as argilas pilarizadas com Cobalto e Ferro. Para o preparo, foram utilizadas argilas naturais de quatro regiões diferentes no Cazaquistão: Akzhar, Asa, Karatau e Kokshetau. A análise de FTIR mostrou que as argilas pilarizadas possuem uma maior quantidade de Ferro na sua estrutura quando comparado com os outros materiais, o que pode indicar que o processo de intercalação do metal na estrutura da argila obteve sucesso. Os resultados obtidos para as isotermas de adsorção de N2 foram usados para classificar o material como Tipo II, atribuída a materiais macroporoso. A caracterização ácida mostrou que os procedimentos usados para preparar a argila pilarizada e a argila ativada causaram modificações estruturais no material. Após a preparação e caracterização, as argilas pilarizadas foram testadas na degradação do paracetamol por meio da catálise húmida com peróxido de hidrogênio. A fim de avaliar a variação da concentração de paracetamol, peróxido de hidrogênio e a variação do teor de carbono orgânico total, amostras foram coletadas em diferentes tempos. O material com a melhor atividade foi a amostra de argila Kokshetau pilarizada (KOP), apresentando uma conversão completa do poluente entre 240 e 360 minutos de reação e uma quantidade de Ferro lixiviado de 0.011%. Essa porcentagem de lixiviação deixou o sistema reativo com uma concentração de Ferro de 0.089 mg/L, um valor menor que o valor limite estabelecido pela legislação (2 mg/L). Como entre as pilarizadas a amostra de Kokshetau demonstrou o melhor resultado, outras amostras a base de Kokshetau (ativada, calcinada e natural) também foram testadas na CWPO do paracetamol. O melhor desempenho da Kokshetau pilarizada pode ser justificado pelo fato de o material possuir uma maior quantidade de acidez, basicidade e área superficial com relação as outras argilas pilarizadas.To VALORCOMP for the financial support and to LSRE-LCM for the opportunity to acquire knowledge in the catalysis field

Execution time as a key parameter in the waste collection problem

Proper waste management has been recognized as a tool for the green transition towards a more sustainable economy. For instance, most studies dealing with municipal solid wastes in the literature focus on environmental aspects, proposing new routes for recycling, composting and landfilling. However, there are other aspects to be improved in the systems that deal with municipal solid waste, especially in the transportation sector. Scholars have been exploring alternatives to improve the performance in waste collection tasks since the late 50s, for example, considering the waste collection problem as static. The transition from a static approach to a dynamic is necessary to increase the feasibility of the solution, requiring faster algorithms. Here we explore the improvement in the performance of the guided local search metaheuristic available in OR-Tools upon different execution times lower than 10 seconds to solve the capacitated waste collection problem. We show that increasing the execution time from 1 to 10 seconds can overcome savings of up to 1.5 km in the proposed system. Considering application in dynamic scenarios, the 9 s increase in execution time (from 1 to 10 s) would not hinder the algorithm’s feasibility. Additionally, the assessment of the relation between performance in different execution times with the dataset’s tightness revealed a correlation to be explored in more detail in future studies. The work done here is the first step towards a shift of paradigm from static scenarios in waste collection to dynamic route planning, with the execution time established according to the conclusions achieved in this study.This work has been supported by FCT—Fundação para a Ciência e a Tecnologia within the R&D Units Project Scope: UIDB/05757/2020, UIDP/05757/2020, UIDB/00690/2020, UIDB/50020/2020, and LA/P/0007/2021. Adriano Silva was supported by FCT-MIT Portugal Ph.D. grant SFRH/BD/151346/2021.info:eu-repo/semantics/publishedVersio

On Separating Environmental and Speaker Adaptation

This paper presents a maximum likelihood (ML) approach, concerned to the background model estimation, in noisy acoustic non-stationary environments. The external noise source is characterised by a time constant convolutional and a time varying additive components. The HMM composition technique, provides a mechanism for integrating parametric models of acoustic background with the signal model, so that noise compensation is tightly coupled with the background model estimation. However, the existing continuous adaptation algorithms usually do not take advantage of this approach, being essentially based on the MLLR algorithm. Consequently, a model for environmental mismatch is not available and, even under constrained conditions a significant number of model parameters have to be updated. From a theoretical point of view only the noise model parameters need to be updated, being the clean speech ones unchanged by the environment. So, it can be advantageous to have a model for environmental mismatch. Additionally separating the additive and convolutional components means a separation between the environmental mismatch and speaker mismatch when the channel does not change for long periods. This approach was followed in the development of the algorithm proposed in this paper. One drawback sometimes attributed to the continuous adaptation approach is that recognition failures originate poor background estimates. This paper also proposes a MAP-like method to deal with this situation

Spectral multi-normalisation for robust speech recognition

This paper presents an improved version of a spectral normalisation based method for extraction of speech robust features in additive noise. The baseline normalisation method was developed by taking into consideration that, while the speech regions with less energy need more robustness, since in these regions the noise is more dominant, the “peaked” spectral regions which are the most reliable due to the higher speech energy must also be preserved as much as possible by the feature extraction process. The additive noise effect tends to flatten the “peaked” spectral zones while the spectral zones of less energy are usually raised. The algorithm proposed in this paper showed to alleviate the noise effect by emphasising the voiced nature of the speech signal by raising the spectral “peaks”, which are “flatten” by the noise effect. The clean speech database is assumed as lightly contaminated, the additive noise is estimated in a frame by frame basis and then used to restore both the “peaked” and the flat spectral zones of the speech spectrum

Spectral normalization MFCC derived features for robust speech recognition

This paper presents a method for extracting MFCC parameters from a normalised power spectrum density. The underlined spectral normalisation method is based on the fact that the speech regions with less energy need more robustness, since in these regions the noise is more dominant, thus the speech is more corrupted. Less energy speech regions contain usually sounds of unvoiced nature where are included nearly half of the consonants, and are by nature the least reliable ones due to the effective noise presence even when the speech is acquired under controlled conditions. This spectral normalisation was tested under additive artificial white noise in an Isolated Speech Recogniser and showed very promising results [1]. It is well known that concerned to speech representation, MFCC parameters appear to be more effective than power spectrum based features. This paper shows how the cepstral speech representation can take advantage of the above-referred spectral normalisation and shows some results in the continuous speech recognition paradigm in clean and artificial noise conditions

Blind source separation by independent component analysis applied to electroencephalographic signals

Independent Component Analysis (ICA) is a statistical based method, which goal is to find a linear transformation to apply to an observed multidimensional random vector such that its components become as statistically independent from each other as possible. Usually the Electroencephalographic (EEG) signal is hard to interpret and analyse since it is corrupted by some artifacts which originates the rejection of contaminated segments and perhaps in an unacceptable loss of data. The ICA filters trained on data collected during EEG sessions can identify statistically independent source channels which could then be further processed by using event-related potential (ERP), event-related spectral perturbation (ERSP) or other signal processing techniques. This paper describes, as a preliminary work, the application of ICA to EEG recordings of the human brain activity, showing its applicability

Genome-wide association studies identify heavy metal ATPase3 as the primary determinant of natural variation in leaf cadmium in Arabidopsis thaliana

Peer reviewedPublisher PD

New magnetic clays MnFe2O4/Shymkent for removal of heavy metals from wastewater

This paper reports the development of a new method. Production of modified clay with magnetic properties based on natural clay from the Shymkent deposit (MnFe2O4/Shymkent nanocomposite), determination of its chemical composition and structure, as well as the study of basic physicochemical properties. The resulting magnetic nanocomposite was then used as an adsorbent to remove nickel (II) ions from wastewater. The prepared magnetic nano composite was then used as adsorbent to remove Ni (II) ions from wastewater, and the optimal conditions for determining thermodynamic and kinetic parameters were evaluated. It was determined that the natural сlay from the Shymkent deposit is a promising material for the modification of the materials. The advantage of such magnetic adsorbents in comparison with the natural materials used as adsorbents is their higher adsorption capacity and theability to control them using a magnetic field. To characterize the modified adsorbents, various assays were used, such as EMP andXRD analysis. The textural properties of the materials were determined by analyzing N2 adsorption-desorption isotherms at 77 K. It is shown that almost all textural and adsorption characteristics of MnFe2O4/Shymkent have significantly improved as a result of the modification made. It was concluded that the MnFe2O4/Shymkent adsorbent obtained in the work can be used for effective wastewater treatment to remove nickel ions.This research is funded by the Science Committee of the Ministry of Education and Science of the Republic of Kazakhstan (Grant No. AP13067715) and by Base Funding of CIMO (UIDB/00690/2020) through FEDER under Program PT2020info:eu-repo/semantics/publishedVersio

Electricity generation from biogas on swine farm considering the regulation of distributed energy generation in Brazil: a case study for Minas Gerais

The objective of this study was to analyze the feasibility of using agricultural waste from a swine farm to produce biogas, which can be used to generate electricity. For this purpose, the waste production potential was evaluated to determine the biogas production capacity of the farm. This measurement allowed scaling the size of the generator used to the electricity production to meet the needs of the farm as well as surplus electricity. The surplus electricity may be used on the farm when the generator is under maintenance or the electricity consumption is larger than the energy generated. This process is regulated by Normative Resolutions 482 and 687 in Brazil. The results of the analysis of the net present value, internal return rate, payback period and benefit cost ratio indicated that the project was feasible

Toxicity of neem oil to the cassava green mite Mononychellus tanajoa (Bondar) (Acari: Tetranychidae)

O artigo não contém o resumo português.Neem (Azadirachta indica A. Juss.)-derived pesticides have been used against a wide range of agricultural pests including tetranychid mites. Approaches combining lethal and sublethal toxicity studies of neem pesticides towards tetranychid mites are necessary to a comprehensive evaluation of such products. Here, we evaluated the lethal and sublethal toxicity of the neem oil Bioneem to the cassava green mite Mononychellus tanajoa (Bondar) by integrating lethal concentration (LC) with population growth and biological parameter studies. According to Probit analyses the concentration of neem oil Bioneem which kills 50% of the population (LC50) of M. tanajoa was 3.28 μL cm^-2, which is roughly twice the field concentration recommended of this biopesticide to control pest mites (1.7 μL cm^-2). The growth rate of the cassava green mite steadily decreased with dosages of neem oil. Furthermore, sublethal concentrations of the neem oil corresponding to the LC50 reduced the periods of the immature stages of M. tanajoa resulting in a shorter developmental time. Similarly, the number of eggs per day and the number of eggs per female per day, a proxy for fecundity, were drastically reduced in M. tanajoa females exposed to the LC50 of neem oil. Based on our comprehensive approach we conclude that the neem oil showed lethal as well as sublethal toxicity on growth rate and biological parameters such as duration of immature stages and fecundity of the cassava green mite M. tanajoa and it could be used as an ecological alternative for the management of this pest