Development of a 1-D Catalyzed Diesel Particulate Filter Model for Simulation of the Performance and the Oxidation of Particulate Matter and Nitrogen Oxides Using Passive Oxidation and Active Regeneration Engine Experimental Data

Back-pressure on a diesel engine equipped with an aftertreatment system is a function of the pressure drop across the individual components of the aftertreatment system, typically, a diesel oxidation catalyst (DOC), catalyzed particulate filter (CPF) and selective catalytic reduction (SCR) catalyst. Pressure drop across the CPF is a function of the mass flow rate and the temperature of the exhaust flowing through it as well as the mass of particulate matter (PM) retained in the substrate wall and the cake layer that forms on the substrate wall. Therefore, in order to control the back-pressure on the engine at low levels and to minimize the fuel consumption, it is important to control the PM mass retained in the CPF. Chemical reactions involving the oxidation of PM under passive oxidation and active regeneration conditions can be utilized with computer numerical models in the engine control unit (ECU) to control the pressure drop across the CPF. Hence, understanding and predicting the filtration and oxidation of PM in the CPF and the effect of these processes on the pressure drop across the CPF are necessary for developing control strategies for the aftertreatment system to reduce back-pressure on the engine and in turn fuel consumption particularly from active regeneration. Numerical modeling of CPF's has been proven to reduce development time and the cost of aftertreatment systems used in production as well as to facilitate understanding of the internal processes occurring during different operating conditions that the particulate filter is subjected to. A numerical model of the CPF was developed in this research work which was calibrated to data from passive oxidation and active regeneration experiments in order to determine the kinetic parameters for oxidation of PM and nitrogen oxides along with the model filtration parameters. The research results include the comparison between the model and the experimental data for pressure drop, PM mass retained, filtration efficiencies, CPF outlet gas temperatures and species (NO2) concentrations out of the CPF. Comparisons of PM oxidation reaction rates obtained from the model calibration to the data from the experiments for ULSD, 10 and 20% biodiesel-blended fuels are presented.

Advanced Methodologies in Dynamic Traffic Assignment Modeling of Managed Lanes

Managed lane strategies are innovative road operation schemes for addressing congestion problems. These strategies operate a lane (lanes) adjacent to a freeway that provides congestion-free trips to eligible users, such as transit or toll-payers. To ensure the successful implementation of managed lanes, the demand on these lanes need to be accurately estimated. Among different approaches for predicting this demand, the four-step demand forecasting process is most common. Managed lane demand is usually estimated at the assignment step. Therefore, the key to reliably estimating the demand is the utilization of effective assignment modeling processes. Managed lanes are particularly effective when the road is functioning at near-capacity. Therefore, capturing variations in demand and network attributes and performance is crucial for their modeling, monitoring and operation. As a result, traditional modeling approaches, such as those used in static traffic assignment of demand forecasting models, fail to correctly predict the managed lane demand and the associated system performance. The present study demonstrates the power of the more advanced modeling approach of dynamic traffic assignment (DTA), as well as the shortcomings of conventional approaches, when used to model managed lanes in congested environments. In addition, the study develops processes to support an effective utilization of DTA to model managed lane operations. Static and dynamic traffic assignments consist of demand, network, and route choice model components that need to be calibrated. These components interact with each other, and an iterative method for calibrating them is needed. In this study, an effective standalone framework that combines static demand estimation and dynamic traffic assignment has been developed to replicate real-world traffic conditions. With advances in traffic surveillance technologies collecting, archiving, and analyzing traffic data is becoming more accessible and affordable. The present study shows how data from multiple sources can be integrated, validated, and best used in different stages of modeling and calibration of managed lanes. Extensive and careful processing of demand, traffic, and toll data, as well as proper definition of performance measures, result in a calibrated and stable model, which closely replicates real-world congestion patterns, and can reasonably respond to perturbations in network and demand properties.

Effects of advanced glycation end-products (AGEs) on retinal pigment epithelial (RPE) cells lysosomal function:implications for age-related macular degeneration (AMD)

Purpose: RPE lysosomal dysfunction is a major contributor to AMD pathogenesis. Controlled activity of a major class of RPE proteinases, the cathepsins, is crucial in maintaining correct lysosomal function. Advanced glycation end-products (AGEs) accumulate in the Bruch’s membrane (BM) with age, impacting critical RPE functions and in turn, contributing to the development of AMD. The aim of this study was to assess the effect of AGEs on lysosomal function by analysing the expression, processing and activity of the cysteine proteinases cathepsins B, L and S, and the aspartic proteinase cathepsin D. Methods: ARPE-19 cells were cultured on AGE-containing BM mimics (matrigel) for 14 days and compared to untreated substrate. Expression levels and intracellular processing of cathepsins B, D, L and S, were assessed by qPCR and immunoblotting of cell lysates. Lysosomal activity was investigated using multiple activity assays specific to each of the analysed cathepsins. Statistical analysis was performed using the Student’s independent T-test. Results: AGE exposure produced a 36% decrease in cathepsin L activity when compared to non-treated controls (p=0.02, n= 3) although no significant changes were observed in protein expression/processing under these conditions. Both the pro and active forms of cathepsin S decreased by 40% (p=0.04) and 74% (p=0.004), respectively (n=3). In contrast, the active form of the cathepsin D increased by 125% (p=0.005, n= 4). However, no changes were observed in the activity levels of both cathepsins S and D. In addition, cathepsin B expression, processing and activity also remained unaltered following AGE exposure. Conclusions: AGEs accumulation in the extracellular matrix, a phenomenon associated with the natural aging process of the BM, attenuates the expression, intracellular processing and activity of specific lysosomal effectors. Altered enzymatic function may impair important lysosomal processes such as endocytosis, autophagy and phagocytosis of photoreceptor outer segments, each of which may influence the age-related dysfunction of the RPE and subsequently, AMD pathogenesis.

Advanced Spectroscopy for the Study of Colourants in Cultural Heritage

Colourants are substances used to change the colour of something, and are classified in three typology of colorants: a) pigments, b) dyes, and c) lakes and hybrid pigments. Their identification is very important when studying cultural heritage; it gives information about the artistic technique, can help in dating, and offers insights on the condition of the object. Besides, the study of the degradation phenomena constitutes a framework for the preventive conservation strategies, provides evidence of the object's original appearance, and contributes to the authentication of works of art. However, the complexity of these systems makes it impossible to achieve a complete understanding using a single technique, making necessary a multi-analytical approach. This work focuses on the set-up and application of advanced spectroscopic methods for the study of colourants in cultural heritage. The first chapter presents the identification of modern synthetic organic pigments using Metal Underlayer-ATR (MU-ATR), and the characterization of synthetic dyes extracted from wool fibres using a combination of Thin Layer Chromatography (TLC) coupled to MU-ATR using AgI@Au plates. The second chapter presents the study of the effect of metallic Ag in the photo-oxidation process of orpiment, and the influence of the different factors, such as light and relative humidity. We used a combination of vibrational and synchrotron radiation-based X-ray microspectroscopy techniques: µ-ATR-FT-IR, µ-Raman, SR-µ-XRF, µ-XANES at S K-, Ag L3- and As K-edges and SR-µ-XRD. The third chapter presents the study of metal carboxylates in paintings, specifically on the formation of Zn and Pb carboxylates in three different binders: stand linseed oil, whole egg, and beeswax. We used micro-ATR-FT-IR, macro FT-IR in total reflection (rMA-FT-IR), portable Near-Infrared spectroscopy (NIR), macro X-ray Powder Diffraction (MA-XRPD), XRPD, and Gas Chromatography Mass-Spectrometry (GC-MS). For the data processing, we explored the data from rMA-FT-IR and NIR with the Principal Component Analysis (PCA).

Investigation of gold-based catalysts for liquid phase oxidation of glucose to glucaric acid

Glucaric acid (GA) is one of the building block chemicals derived from sugar biomass with higher added value. Nowadays, GA is produced by oxidation of glucose (Glu) with either stoichiometric oxidants (HNO3), or by means of electrochemical or biochemical synthesis. However, these processes show drawbacks from either the environmental or economic viewpoint. For this reason, gold nanoparticles (Au NPs) supported on activated carbon (AC) have been studied as catalysts for the oxidation of Glu, using O2 as oxidant in the presence of a base. Using sol immobilization technique, Au NPs have been supported on AC following different experimental procedures. UV-Vis spectroscopy, XRD, TEM and TG analysis were utilized in the characterization of the catalysts. The operational conditions were optimized obtaining 24% of yield of GA, 37% to GO and 27% to byproducts in 1 h, 1000 rpm, 10 bar of O2 and Glu:Au:NaOH molar ratio of 1000:1:3000. Under such conditions, catalysts show relatively high Glu conversion (≥82%) with different GA yields. GO+GA yield is around 58-61%. Therefore, the oxidation reaction was performed at 15 min where Au/AC PVA0 reached the highest yield of GA (16%) and Au/AC PVA2.4 gave the lowest (8%). It is evident that the presence of PVA influences to a higher degree the reaction rate than the Au NPs size. Hence, the effect of different heat treatments where applied for the removal of PVA: washing with water at 60℃ or heat treatment (120-250℃) with Air/H2. Washing treatment and heat treatment at 120℃ with Air/H2 may have resulted in the mildest treatments for the removal of PVA. Finally, two different supports have been used in order to study the effect of metal-support interaction in the immobilization of Au NPs: ZrO2 and AC. Au/AC catalyst demonstrated a higher conversion of GO to GA at short reaction times (15.1% yield GA) compared to Au/ZrO2 (2.4% yield GA).

Supported metal nanoparticles for sustainable green catalytic processes

Preformed Au nanoparticles supported on activated carbon and TiO2 were synthesised by sol-immobilisation. Polyethylene glycol, polyvinyl pyrrolidone and polyvinyl alcohol were used as stabilisers for the gold nanoparticles at different polymer/Au wt/wt ratios for each polymer. The effect of polymer/Au wt/wt ratios was investigated on (i) the average nanoparticle size, (ii) catalytic activity for two reactions, 4-nitrophenol reduction and glucose oxidation to glucaric acid. 4-nitrophenol reduction is recognised as a model reaction for nanomaterial catalytic activity tests; glucose oxidation to glucaric acid is a reaction that is traditionally carried out with concentrated nitric acid, for which alternative reaction pathways are looked for in an effort to reduce its environmental impact. The catalysts were characterised from the nanoparticle synthesis by colloidal method by means of UV-vis spectroscopy and DLS analysis, to the immobilisation step by XRD and TEM. The effect of the polymer:Au wt/wt ratio on nanoparticle size depends on the polymer nature, and point out the need to optimise supported nanoparticle synthesis protocols in the future depending on the type of stabiliser. The catalytic tests revealed that the polymers interact with Au nanoparticles through different active sites. Activated carbon (AC) and TiO2 were compared as supports for Au nanoparticles stabilised by PVA at PVA/Au 0,65 wt/wt. AC-supported Au NPs were the most active for glucose oxidation while TiO2-stabilised Au NPs were five times more active in 4-nitrophenol reduction that AC-supported NPs. Hence support and stabiliser are important parameters that should be optimised in order to achieve high catalytic activity for a given reaction.

Design and Off-design modelling of advanced Power-to-Gas energy storage systems

Power-to-Gas storage systems have the potential to address grid-stability issues that arise when an increasing share of power is generated from sources that have a highly variable output. Although the proof-of-concept of these has been promising, the behaviour of the processes in off-design conditions is not easily predictable. The primary aim of this PhD project was to evaluate the performance of an original Power-to-Gas system, made up of innovative components. To achieve this, a numerical model has been developed to simulate the characteristics and the behaviour of the several components when the whole system is coupled with a renewable source. The developed model has been applied to a large variety of scenarios, evaluating the performance of the considered process and exploiting a limited amount of experimental data. The model has been then used to compare different Power-to-Gas concepts, in a real scenario of functioning. Several goals have been achieved. In the concept phase, the possibility to thermally integrate the high temperature components has been demonstrated. Then, the parameters that affect the energy performance of a Power-to-Gas system coupled with a renewable source have been identified, providing general recommendations on the design of hybrid systems; these parameters are: 1) the ratio between the storage system size and the renewable generator size; 2) the type of coupled renewable source; 3) the related production profile. Finally, from the results of the comparative analysis, it is highlighted that configurations with a highly oversized renewable source with respect to the storage system show the maximum achievable profit.

Advanced voxel-based CAD modelling for FSI simulations for automotive structures design

Additive Manufacturing (AM) is nowadays considered an important alternative to traditional manufacturing processes. AM technology shows several advantages in literature as design flexibility, and its use increases in automotive, aerospace and biomedical applications. As a systematic literature review suggests, AM is sometimes coupled with voxelization, mainly for representation and simulation purposes. Voxelization can be defined as a volumetric representation technique based on the model’s discretization with hexahedral elements, as occurs with pixels in the 2D image. Voxels are used to simplify geometric representation, store intricated details of the interior and speed-up geometric and algebraic manipulation. Compared to boundary representation used in common CAD software, voxel’s inherent advantages are magnified in specific applications such as lattice or topologically structures for visualization or simulation purposes. Those structures can only be manufactured with AM employment due to their complex topology. After an accurate review of the existent literature, this project aims to exploit the potential of the voxelization algorithm to develop optimized Design for Additive Manufacturing (DfAM) tools. The final aim is to manipulate and support mechanical simulations of lightweight and optimized structures that should be ready to be manufactured with AM with particular attention to automotive applications. A voxel-based methodology is developed for efficient structural simulation of lattice structures. Moreover, thanks to an optimized smoothing algorithm specific for voxel-based geometries, a topological optimized and voxelized structure can be transformed into a surface triangulated mesh file ready for the AM process. Moreover, a modified panel code is developed for simple CFD simulations using the voxels as a discretization unit to understand the fluid-dynamics performances of industrial components for preliminary aerodynamic performance evaluation. The developed design tools and methodologies perfectly fit the automotive industry’s needs to accelerate and increase the efficiency of the design workflow from the conceptual idea to the final product.

Processi e pratiche di Innovazione Responsabile: il ruolo dell' Advanced Design nella trasformazione collaborativa dei territori

La ricerca indaga il rapporto tra Design e Innovazione Responsabile calandolo all’interno della relazione tra territorio e pratiche collaborative guidate dal design, ma anche legate al patrimonio culturale immateriale e a un sistema di conoscenza a quintupla elica. La necessità emergente di cura del futuro porta a rivedere il contesto del territorio come campo strumentale per la trasformazione degli individui e della comunità e a domandarsi in che modo il design possa supportare questo cambiamento, abilitando la produzione di conoscenza collaborativa. La ricerca parte dal dimostrare come il modello di innovazione recentemente proposto dalla Comunità Europea attraverso il concetto di Responsible Research Innovation (RRI), poi ripreso nella nozione di Responsible Innovation (RI), sia un campo aperto e responsivo: se integrato con altre discipline, in particolare con il design, può supportare lo sviluppo di processi, politiche, prodotti, servizi e comportamenti che rispettino la relazione tra società, ambiente, identità individuale e collettiva e i ritmi ad essi connessi. Partendo dal contesto sopra descritto, ci si chiede come il design e il designer possano integrare le dimensioni RI nei processi di progettazione, per innovare in modo collaborativo i territori. Si individua quindi nell’Advanced Design la metodologia che, grazie alla sua natura anticipatrice, collaborativa, trasformativa, riesce a coniugarsi virtuosamente con l’approccio RI e supportare il cambiamento in atto. L’intersezione di questi elementi porta alla creazione del Modello Advanced Design per/con l’Innovazione Responsabile (ADIR): un sistema multidimensionale per gruppi di innovazione (quintupla elica) che hanno l’obiettivo di rigenerare in modo collaborativo e inclusivo i territori. L’esperienza sul campo ha confermato come la struttura del modello, formata da un corpus di semi-lavorati, permetta di creare un proprio ritmo, una compenetrazione tra azioni e forme progettuali volti a mantenere il senso di comunità e il coinvolgimento degli attori, a creare relazioni, a sviluppare una trasformazione continua.

Development of functional MRI protocols in the study of neurodegenerative diseases: MRI study in patients with REM sleep behavior disorder, idiopathic Parkinson's disease and multisystem atrophy

In the central nervous system, iron in several proteins is involved in many important processes: oxygen transportation, oxidative phosphorylation, mitochondrial respiration, myelin production, the synthesis and metabolism of neurotransmitters. Abnormal iron homoeostasis can induce cellular damage through hydroxyl radical production, which can cause the oxidation, modification of lipids, proteins, carbohydrates, and DNA, lead to neurotoxicity. Moreover increased levels of iron are harmful and iron accumulations are typical hallmarks of brain ageing and several neurodegenerative disorders particularly PD. Numerous studies on post mortem tissue report on an increased amount of total iron in the substantia nigra in patients with PD also supported by large body of in vivo findings from Magnetic Resonance Imaging (MRI) studies. The importance and approaches for in vivo brain iron assessment using multiparametric MRI is increased over last years. Quantitative MRI may provide useful biomarkers for brain integrity assessment in iron-related neurodegeneration. Particularly, a prominent change in iron- sensitive T2* MRI contrast within the sub areas of the SN overlapping with nigrosome 1 were shown to be a hallmark of Parkinson's Disease with high diagnostic accuracy. Moreover, differential diagnosis between Parkinson's Disease (PD) and atypical parkinsonian syndromes (APS) remains challenging, mainly in the early phases of the disease. Advanced brain MR imaging enables to detect the pathological changes of nigral and extranigral structures at the onset of clinical manifestations and during the course of the disease. The Nigrosome-1 (N1) is a substructure of the healthy Substantia Nigra pars compacta enriched by dopaminergic neurons; their loss in Parkinson’s disease and atypical parkinsonian syndromes is related to the iron accumulation. N1 changes are supportive MR biomarkers for diagnosis of these neurodegenerative disorders, but its detection is hard with conventional sequences, also using high field (3T) scanner. Quantitative susceptibility mapping (QSM), an iron-sensitive technique, enables the direct detection of Neurodegeneration

Analytics and optimization for emergency healthcare processes

This thesis deals with the analysis and management of emergency healthcare processes through the use of advanced analytics and optimization approaches. Emergency processes are among the most complex within healthcare. This is due to their non-elective nature and their high variability. This thesis is divided into two topics. The first one concerns the core of emergency healthcare processes, the emergency department (ED). In the second chapter, we describe the ED that is the case study. This is a real case study with data derived from a large ED located in northern Italy. In the next two chapters, we introduce two tools for supporting ED activities. The first one is a new type of analytics model. Its aim is to overcome the traditional methods of analyzing the activities provided in the ED by means of an algorithm that analyses the ED pathway (organized as event log) as a whole. The second tool is a decision-support system, which integrates a deep neural network for the prediction of patient pathways, and an online simulator to evaluate the evolution of the ED over time. Its purpose is to provide a set of solutions to prevent and solve the problem of the ED overcrowding. The second part of the thesis focuses on the COVID-19 pandemic emergency. In the fifth chapter, we describe a tool that was used by the Bologna local health authority in the first part of the pandemic. Its purpose is to analyze the clinical pathway of a patient and from this automatically assign them a state. Physicians used the state for routing the patients to the correct clinical pathways. The last chapter is dedicated to the description of a MIP model, which was used for the organization of the COVID-19 vaccination campaign in the city of Bologna, Italy.

Data assimilation for advanced cross-scale unstructured-grid ocean modeling.

The coastal ocean is a complex environment with extremely dynamic processes that require a high-resolution and cross-scale modeling approach in which all hydrodynamic fields and scales are considered integral parts of the overall system. In the last decade, unstructured-grid models have been used to advance in seamless modeling between scales. On the other hand, the data assimilation methodologies to improve the unstructured-grid models in the coastal seas have been developed only recently and need significant advancements. Here, we link the unstructured-grid ocean modeling to the variational data assimilation methods. In particular, we show results from the modeling system SANIFS based on SHYFEM fully-baroclinic unstructured-grid model interfaced with OceanVar, a state-of-art variational data assimilation scheme adopted for several systems based on a structured grid. OceanVar implements a 3DVar DA scheme. The combination of three linear operators models the background error covariance matrix. The vertical part is represented using multivariate EOFs for temperature, salinity, and sea level anomaly. The horizontal part is assumed to be Gaussian isotropic and is modeled using a first-order recursive filter algorithm designed for structured and regular grids. Here we introduced a novel recursive filter algorithm for unstructured grids. A local hydrostatic adjustment scheme models the rapidly evolving part of the background error covariance. We designed two data assimilation experiments using SANIFS implementation interfaced with OceanVar over the period 2017-2018, one with only temperature and salinity assimilation by Argo profiles and the second also including sea level anomaly. The results showed a successful implementation of the approach and the added value of the assimilation for the active tracer fields. While looking at the broad basin, no significant improvements are highlighted for the sea level, requiring future investigations. Furthermore, a Machine Learning methodology based on an LSTM network has been used to predict the model SST increments.

Electrochemistry of polycyclic aromatic molecules for advanced carbon nanostructures: luminescence and transistor applications

Polycyclic aromatic hydrocarbons (PAHs) are a large class of π-conjugated organic molecules with fused aromatic rings, which can be considered as fragments of 2D-graphene and have been extensively studied for their unique optical and electronic properties. The aim of this study is to understand the complex electrochemical behaviour of planar, curved, and heteroatom doped polycyclic aromatic molecules, particularly focusing on the oxidative coupling of their radical cations and the electrochemically induced cyclodehydrogenation reactions. In the first part of this thesis, the class of PAHs and aromatic nanostructures are introduced, and the reactivity of electrogenerated species is discussed, focusing on the electrochemical approach for the synthesis of extended π-conjugated structures. Subsequently, the electrochemical properties and reactivity of electrogenerated radical ions of planar and curved polyaromatics are correlated to their structures. In the third chapter, electrochemical cyclodehydrogenation of hexaphenylbenzene is used to prepare self-assembled hexabenzocoronene, directly deposited on an interdigitated electrode, which was characterised as organic electrochemical transistor. In the fourth chapter, the electrochemical behaviour of a family of azapyrene derivatives has been carefully investigated together with the electrogenerated chemiluminescence (ECL), both by ion-annihilation and co-reactant methods. Two structural azapyrene isomers with different nitrogen positions are thoroughly discussed in terms of redox and ECL properties. Interestingly, the ECL of only one of them showed a double emission with excimer formation. A detailed mechanism is discussed for the ECL by co-reactant benzoyl peroxide, to rationalise the different ECL behaviours of the two isomers on the basis of their topologically modulated electronic properties. In conclusion, the different electrochemical behaviours of PAHs were shown, focussing on the chemical reactivity of the electrogenerated species and taking advantage of it for important processes spanning from unconventional synthesis methods for carbon nanostructures to the exploitation of self-assembled nanostructured systems in organic electronics, to novel organic emitters in ECL.

Electrochemical oxidation of Kraft and Dealkaline lignin to produce value-added chemicals on Nickel electrocatalysts

One of the most important scientific and environmental issues is reducing global dependence on fossil sources and one of the solutions is to use biomass as feedstock. In particular, the use of lignocellulosic biomass to obtain molecules with considerable commercial importance is gaining more and more interest. Lignin, the most recalcitrant part of lignocellulosic biomass, is a valuable source of sustainable and renewable aromatic molecules, currently produced from petrochemical processes. Vanillin, one of the most important aromatic aldehydes on an industrial level, can be obtained through catalytic lignin oxidation. An alternative to the conventional catalytic oxidation process is the electro-catalytic process, which can be carried out at ambient temperature and pressure, using water as solvent, and it can be considered as a renewable energy storage. In this thesis, the electrocatalytic oxidation of Kraft and Dealkaline lignin in NaOH was investigated over Ni foam catalysts. The effect of the reaction parameters (i.e. time, applied potential, lignin concentration, NaOH concentration, and temperature) on the yields of vanillin and other valuable products was evaluated. After the screening of the reaction conditions, a systematic study of the contribution of the homogeneous reaction (lignin depolymerization due to the basic solvent) to the yield of the product was accomplished. Finally, considering the obtained results, an alternative reaction procedure was proposed.

Geochemistry Of Acid Mine Drainage From A Coal Mining Area And Processes Controlling Metal Attenuation In Stream Waters, Southern Brazil.

Acid drainage influence on the water and sediment quality was investigated in a coal mining area (southern Brazil). Mine drainage showed pH between 3.2 and 4.6 and elevated concentrations of sulfate, As and metals, of which, Fe, Mn and Zn exceeded the limits for the emission of effluents stated in the Brazilian legislation. Arsenic also exceeded the limit, but only slightly. Groundwater monitoring wells from active mines and tailings piles showed pH interval and chemical concentrations similar to those of mine drainage. However, the river and ground water samples of municipal public water supplies revealed a pH range from 7.2 to 7.5 and low chemical concentrations, although Cd concentration slightly exceeded the limit adopted by Brazilian legislation for groundwater. In general, surface waters showed large pH range (6 to 10.8), and changes caused by acid drainage in the chemical composition of these waters were not very significant. Locally, acid drainage seemed to have dissolved carbonate rocks present in the local stratigraphic sequence, attenuating the dispersion of metals and As. Stream sediments presented anomalies of these elements, which were strongly dependent on the proximity of tailings piles and abandoned mines. We found that precipitation processes in sediments and the dilution of dissolved phases were responsible for the attenuation of the concentrations of the metals and As in the acid drainage and river water mixing zone. In general, a larger influence of mining activities on the chemical composition of the surface waters and sediments was observed when enrichment factors in relation to regional background levels were used.