Search results for: pollutant

Authors: E. Carraro, Sa. Bonetta, Si. Bonetta, E. Ceretti, G. C. V. Viola, C. Pignata, S. Levorato, T. Salvatori, S. Vannini, V. Romanazzi, A. Carducci, G. Donzelli, T. Schilirò, A. De Donno, T. Grassi, S. Bonizzoni, A. Bonetti, G. Gilli, U. Gelatti

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In 2013, air pollution and particulate matter were classified as carcinogenic to human by the IARC. At present, PM is Europe's most problematic pollutant in terms of harm to health, as reported by European Environmental Agency (EEA) in the EEA Technical Report on Air quality in Europe, 2015. A percentage between 17-30 of the EU urban population lives in areas where the EU air quality 24-hour limit value for PM10 is exceeded. Many studies have found a consistent association between exposure to PM and the incidence and mortality for some chronic diseases (i.e. lung cancer, cardiovascular diseases). Among the mechanisms responsible for these adverse effects, genotoxic damage is of particular concern. Children are a high-risk group in terms of the health effects of air pollution and early exposure during childhood can increase the risk of developing chronic diseases in adulthood. The MAPEC_LIFE (Monitoring Air Pollution Effects on Children for supporting public health policy) is a project founded by EU Life+ Programme (LIFE12 ENV/IT/000614) which intends to evaluate the associations between air pollution and early biological effects in children and to propose a model for estimating the global risk of early biological effects due to air pollutants and other factors in children. This work is focused on the micronuclei frequency in child buccal cells in association with airborne PM levels taking into account the influence of other factors associated with the lifestyle of children. The micronucleus test was performed in exfoliated buccal cells of 6–8 years old children from 5 Italian towns with different air pollution levels. Data on air quality during the study period were obtained from the Regional Agency for Environmental Protection. A questionnaire administered to children’s parents was used to obtain details on family socio-economic status, children health condition, exposures to other indoor and outdoor pollutants (i.e. passive smoke) and life-style, with particular reference to eating habits. During the first sampling campaign (winter 2014-15) 1315 children were recruited and sampled for Micronuclei test in buccal cells. In the sampling period the levels of the main pollutants and PM10 were, as expected, higher in the North of Italy (PM10 mean values 62 μg/m3 in Torino and 40 μg/m3 in Brescia) than in the other towns (Pisa, Perugia, Lecce). A higher Micronucleus frequency in buccal cells of children was found in Brescia (0.6/1000 cells) than in the other towns (range 0.3-0.5/1000 cells). The statistical analysis underlines a relation of the micronuclei frequency with PM concentrations, traffic level near child residence, and level of education of parents. The results suggest that, in addition to air pollution exposure, some other factors, related to lifestyle or further exposures, may influence micronucleus frequency and cellular response to air pollutants.

Keywords: air pollution, buccal cells, children, micronucleus cytome assay

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Authors: Vittorio Astarita, Giuseppe Guido, Vincenzo Pasquale Giofre, Alessandro Vitale

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Traffic microsimulation has been used extensively to evaluate consequences of different traffic planning and control policies in terms of travel time delays, queues, pollutant emissions, and every other common measured performance while at the same time traffic safety has not been considered in common traffic microsimulation packages as a measure of performance for different traffic scenarios. Vehicle conflict techniques that were introduced at intersections in the early traffic researches carried out at the General Motor laboratory in the USA and in the Swedish traffic conflict manual have been applied to vehicles trajectories simulated in microscopic traffic simulators. The concept is that microsimulation can be used as a base for calculating the number of conflicts that will define the safety level of a traffic scenario. This allows engineers to identify unsafe road traffic maneuvers and helps in finding the right countermeasures that can improve safety. Unfortunately, most commonly used indicators do not consider conflicts between single vehicles and roadside obstacles and barriers. A great number of vehicle crashes take place with roadside objects or obstacles. Only some recent proposed indicators have been trying to address this issue. This paper introduces a new procedure based on the simulation of potential crash events for the evaluation of safety levels in microsimulation traffic scenarios, which takes into account also potential crashes with roadside objects and barriers. The procedure can be used to define new conflict indicators. The proposed simulation procedure generates with the random perturbation of vehicle trajectories a set of potential crashes which can be evaluated accurately in terms of DeltaV, the energy of the impact, and/or expected number of injuries or casualties. The procedure can also be applied to real trajectories giving birth to new surrogate safety performance indicators, which can be considered as “simulation-based”. The methodology and a specific safety performance indicator are described and applied to a simulated test traffic scenario. Results indicate that the procedure is able to evaluate safety levels both at the intersection level and in the presence of roadside obstacles. The procedure produces results that are expressed in the same unity of measure for both vehicle to vehicle and vehicle to roadside object conflicts. The total energy for a square meter of all generated crash can be used and is shown on the map, for the test network, after the application of a threshold to evidence the most dangerous points. Without any detailed calibration of the microsimulation model and without any calibration of the parameters of the procedure (standard values have been used), it is possible to identify dangerous points. A preliminary sensitivity analysis has shown that results are not dependent on the different energy thresholds and different parameters of the procedure. This paper introduces a specific new procedure and the implementation in the form of a software package that is able to assess road safety, also considering potential conflicts with roadside objects. Some of the principles that are at the base of this specific model are discussed. The procedure can be applied on common microsimulation packages once vehicle trajectories and the positions of roadside barriers and obstacles are known. The procedure has many calibration parameters and research efforts will have to be devoted to make confrontations with real crash data in order to obtain the best parameters that have the potential of giving an accurate evaluation of the risk of any traffic scenario.

Keywords: road safety, traffic, traffic safety, traffic simulation

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Authors: F. Portet-Koltalo, Y. Tian, I. Berger, C. Boulanger-Lecomte, A. Benamar, N. Machour

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Sediments are complex environments which can accumulate a great variety of persistent toxic contaminants such as polychlorobiphenyles (PCBs), polycyclic aromatic hydrocarbons (PAHs) and some of their more toxic degradation metabolites such as hydroxylated PAHs (OH-PAHs). Owing to their composition, fine clayey sediments can be more difficult to extract than soils using conventional solvent extraction processes. So this study aimed to compare the potential of MSPD (matrix solid phase dispersive extraction) to extract PCBs, PAHs and OH-PAHs, in comparison with microwave assisted extraction (MAE). Methodologies: MAE extraction with various solvent mixtures was used to extract PCBs, PAHs and OH-PAHs from sediments in two runs, followed by two GC-MS analyses. MSPD consisted in crushing the dried sediment with dispersive agents, introducing the mixture in cartridges and eluting the target compounds with an appropriate volume of selected solvents. So MSPD combined with cartridges containing MIPs (molecularly imprinted polymers) designed for OH-PAHs was used to extract the three families of target compounds in only one run, followed by parallel analyses in GC-MS for PAHs/PCBs and HPLC-FLD for OH-PAHs. Results: MAE extraction was optimized to extract from clayey sediments, in two runs, PAHs/PCBs in one hand and OH-PAHs in the other hand. Indeed, the best conditions of extractions (mixtures of extracting solvents, temperature) were different if we consider the polarity and the thermodegradability of the different families of target contaminants: PAHs/PCBs were better extracted using an acetone/toluene 50/50 mixture at 130°C whereas OH-PAHs were better extracted using an acetonitrile/toluene 90/10 mixture at 100°C. Moreover, the two consecutive GC-MS analyses contributed to double the total analysis time. A matrix solid phase dispersive (MSPD) extraction procedure was also optimized, with the first objective of increasing the extraction recovery yields of PAHs and PCBs from fine-grained sediment. The crushing time (2-10 min), the nature of the dispersing agents added for purifying and increasing the extraction yields (Florisil, octadecylsilane, 3-chloropropyle, 4-benzylchloride), the nature and the volume of eluting solvents (methylene chloride, hexane, hexane/acetone…) were studied. It appeared that in the best conditions, MSPD was a better extraction method than MAE for PAHs and PCBs, with respectively, mean increases of 8.2% and 71%. This method was also faster, easier and less expensive. But the other advantage of MSPD was that it allowed to introduce easily, just after the first elution process of PAHs/PCBs, a step permitting the selective recovery of OH-PAHs. A cartridge containing MIPs designed for phenols was coupled to the cartridge containing the dispersed sediment, and various eluting solvents, different from those used for PAHs and PCBs, were tested to selectively concentrate and extract OH-PAHs. Thereafter OH-PAHs could be analyzed at the same time than PAHs and PCBs: the OH-PAH extract could be analyzed with HPLC-FLD, whereas the PAHs/PCBs extract was analyzed with GC-MS, adding only few minutes more to the total duration of the analytical process. Conclusion: MSPD associated to MIPs appeared to be an easy, fast and low expensive method, able to extract in one run a complex mixture of toxic apolar and more polar contaminants present in clayey fine-grained sediments, an environmental matrix which is generally difficult to analyze.

Keywords: contaminated fine-grained sediments, matrix solid phase dispersive extraction, microwave assisted extraction, molecularly imprinted polymers, multi-pollutant analysis

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Authors: Michelle E. Taylor, Clare E. Morrall

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Microplastics are small particles produced for industrial purposes or formed by breakdown of anthropogenic debris. Caribbean nations import large quantities of plastic products. The Caribbean region is vulnerable to natural disasters and Climate Change is predicted to bring multiple additional challenges to island nations. Microplastics have been found in an array of marine environments and in a diversity of marine species. Occurrence of microplastic in the intestinal tracts of marine fish is a concern to human and ecosystem health as pollutants and pathogens can associate with plastics. Studies have shown that the incidence of microplastics in marine fish varies with species and location. Prevalence of microplastics (≤ 5 mm) in fish species from Grenadian waters (representing pelagic, semi-pelagic and demersal lifestyles) harvested for human consumption have been investigated via gut analysis. Harvested tissue was digested in 10% KOH and particles retained on a 0.177 mm sieve were examined. Microplastics identified have been classified according to type, colour and size. Over 97% of fish examined thus far (n=34) contained microplastics. Current and future work includes examining the invasive Lionfish (Pterois spp.) for microplastics, investigating marine invertebrate species as well as examining environmental sources of microplastics (i.e. rivers, coastal waters and sand). Owing to concerns of pollutant accumulation on microplastics and potential migration into organismal tissues, we plan to analyse fish tissue for mercury and other persistent pollutants. Despite having ~110,000 inhabitants, the island nation of Grenada imported approximately 33 million plastic bottles in 2013, of which it is estimated less than 5% were recycled. Over 30% of the imported bottles were ‘unmanaged’, and as such are potential litter/marine debris. A revised Litter Abatement Act passed into law in Grenada in 2015, but little enforcement of the law is evident to date. A local Non-governmental organization (NGO) ‘The Grenada Green Group’ (G3) is focused on reducing litter in Grenada through lobbying government to implement the revised act and running sessions in schools, community groups and on local media and social media to raise awareness of the problems associated with plastics. A local private company has indicated willingness to support an Anti-Litter Campaign in 2018 and local awareness of the need for a reduction of single use plastic use and litter seems to be high. The Government of Grenada have called for a Sustainable Waste Management Strategy and a ban on both Styrofoam and plastic grocery bags are among recommendations recently submitted. A Styrofoam ban will be in place at the St. George’s University campus from January 1st, 2018 and many local businesses have already voluntarily moved away from Styrofoam. Our findings underscore the importance of continuing investigations into microplastics in marine life; this will contribute to understanding the associated health risks. Furthermore, our findings support action to mitigate the volume of plastics entering the world’s oceans. We hope that Grenada’s future will involve a lot less plastic. This research was supported by the Caribbean Node of the Global Partnership on Marine Litter.

Keywords: Caribbean, microplastics, pollution, small island developing nation

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Authors: Francesca Gullo, Paola Palmero, Massimo Messori

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Transparent wood is considered a promising structural material for the development of environmentally friendly, energy-efficient engineered components. To obtain transparent wood from natural wood materials two approaches can be used: i) bottom-up and ii) top-down. Through the second method, the color of natural wood samples is lightened through a chemical bleaching process that acts on chromophore groups of lignin, such as the benzene ring, quinonoid, vinyl, phenolics, and carbonyl groups. These chromophoric units form complex conjugate systems responsible for the brown color of wood. There are two strategies to remove color and increase the whiteness of wood: i) lignin removal and ii) lignin bleaching. In the lignin removal strategy, strong chemicals containing chlorine (chlorine, hypochlorite, and chlorine dioxide) and oxidizers (oxygen, ozone, and peroxide) are used to completely destroy and dissolve the lignin. In lignin bleaching methods, a moderate reductive (hydrosulfite) or oxidative (hydrogen peroxide) is commonly used to alter or remove the groups and chromophore systems of lignin, selectively discoloring the lignin while keeping the macrostructure intact. It is, therefore, essential to manipulate nanostructured wood by precisely controlling the nanopores in the cell walls by monitoring both chemical treatments and process conditions, for instance, the treatment time, the concentration of chemical solutions, the pH value, and the temperature. The elimination of wood light scattering is the second step in the fabrication of transparent wood materials, which can be achieved through two-step approaches: i) the polymer impregnation method and ii) the densification method. For the polymer impregnation method, the wood scaffold is treated with polymers having a corresponding refractive index (e.g., PMMA and epoxy resins) under vacuum to obtain the transparent composite material, which can finally be pressed to align the cellulose fibers and reduce interfacial defects in order to have a finished product with high transmittance (>90%) and excellent light-guiding. However, both the solution-based bleaching and the impregnation processes used to produce transparent wood generally consume large amounts of energy and chemicals, including some toxic or pollutant agents, and are difficult to scale up industrially. Here, we report a method to produce optically transparent wood by modifying the lignin structure with a chemical reaction at room temperature using small amounts of hydrogen peroxide in an alkaline environment. This method preserves the lignin, which results only deconjugated and acts as a binder, providing both a strong wood scaffold and suitable porosity for infiltration of biobased polymers while reducing chemical consumption, the toxicity of the reagents used, polluting waste, petroleum by-products, energy and processing time. The resulting transparent wood demonstrates high transmittance and low thermal conductivity. Through the combination of process efficiency and scalability, the obtained materials are promising candidates for application in the field of construction for modern energy-efficient buildings.

Keywords: bleached wood, energy-efficient components, hydrogen peroxide, transparent wood, wood composites

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Authors: Antonella Falanga, Armando Cartenì

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Today, an unprecedented amount of data coming from several sources, including mobile devices, sensors, tracking systems, and online platforms, characterizes our lives. The term “big data” not only refers to the quantity of data but also to the variety and speed of data generation. These data hold valuable insights that, when extracted and analyzed, facilitate informed decision-making. The 4Vs of big data - velocity, volume, variety, and value - highlight essential aspects, showcasing the rapid generation, vast quantities, diverse sources, and potential value addition of these kinds of data. This surge of information has revolutionized many sectors, such as business for improving decision-making processes, healthcare for clinical record analysis and medical research, education for enhancing teaching methodologies, agriculture for optimizing crop management, finance for risk assessment and fraud detection, media and entertainment for personalized content recommendations, emergency for a real-time response during crisis/events, and also mobility for the urban planning and for the design/management of public and private transport services. Big data's pervasive impact enhances societal aspects, elevating the quality of life, service efficiency, and problem-solving capacities. However, during this transformative era, new challenges arise, including data quality, privacy, data security, cybersecurity, interoperability, the need for advanced infrastructures, and staff training. Within the transportation sector (the one investigated in this research), applications span planning, designing, and managing systems and mobility services. Among the most common big data applications within the transport sector are, for example, real-time traffic monitoring, bus/freight vehicle route optimization, vehicle maintenance, road safety and all the autonomous and connected vehicles applications. Benefits include a reduction in travel times, road accidents and pollutant emissions. Within these issues, the proper transport demand estimation is crucial for sustainable transportation planning. Evaluating the impact of sustainable mobility policies starts with a quantitative analysis of travel demand. Achieving transportation decarbonization goals hinges on precise estimations of demand for individual transport modes. Emerging technologies, offering substantial big data at lower costs than traditional methods, play a pivotal role in this context. Starting from these considerations, this study explores the usefulness impact of big data within transport demand estimation. This research focuses on leveraging (big) data collected during the COVID-19 pandemic to estimate the evolution of the mobility demand in Italy. Estimation results reveal in the post-COVID-19 era, more than 96 million national daily trips, about 2.6 trips per capita, with a mobile population of more than 37.6 million Italian travelers per day. Overall, this research allows us to conclude that big data better enhances rational decision-making for mobility demand estimation, which is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, cloud computing, decision-making, mobility demand, transportation

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Authors: Miguel A. Figueroa, José A. Lara-Ramos, Miguel A. Mueses

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Pharmaceutical residues are a section of emerging contaminants of anthropogenic origin that are present in a myriad of waters with which human beings interact daily and are starting to affect the ecosystem directly. Conventional waste-water treatment systems are not capable of degrading these pharmaceutical effluents because their designs cannot handle the intermediate products and biological effects occurring during its treatment. That is why it is necessary to hybridize conventional waste-water systems with non-conventional processes. In the specific case of an ozonation process, its efficiency highly depends on a perfect dispersion of ozone, long times of interaction of the gas-liquid phases and the size of the ozone bubbles formed through-out the reaction system. In order to increase the efficiency of these parameters, the use of a modified flotation cell has been proposed recently as a reactive system, which is used at an industrial level to facilitate the suspension of particles and spreading gas bubbles through the reactor volume at a high rate. The objective of the present work is the development of a mathematical model that can closely predict the kinetic rates of reactions taking place in the flotation cell at an experimental scale by means of identifying proper reaction mechanisms that take into account the modified chemical and hydrodynamic factors in the FeO-catalyzed Ozonation of Diclofenac aqueous solutions in a flotation cell. The methodology is comprised of three steps: an experimental phase where a modified flotation cell reactor is used to analyze the effects of ozone concentration and loading catalyst over the degradation of Diclofenac aqueous solutions. The performance is evaluated through an index of utilized ozone, which relates the amount of ozone supplied to the system per milligram of degraded pollutant. Next, a theoretical phase where the reaction mechanisms taking place during the experiments must be identified and proposed that details the multiple direct and indirect reactions the system goes through. Finally, a kinetic model is obtained that can mathematically represent the reaction mechanisms with adjustable parameters that can be fitted to the experimental results and give the model a proper physical meaning. The expected results are a robust reaction rate law that can simulate the improved results of Diclofenac mineralization on water using the modified flotation cell reactor. By means of this methodology, the following results were obtained: A robust reaction pathways mechanism showcasing the intermediates, free-radicals and products of the reaction, Optimal values of reaction rate constants that simulated Hatta numbers lower than 3 for the system modeled, degradation percentages of 100%, TOC (Total organic carbon) removal percentage of 69.9 only requiring an optimal value of FeO catalyst of 0.3 g/L. These results showed that a flotation cell could be used as a reactor in ozonation, catalytic ozonation and photocatalytic ozonation processes, since it produces high reaction rate constants and reduces mass transfer limitations (Ha > 3) by producing microbubbles and maintaining a good catalyst distribution.

Keywords: advanced oxidation technologies, iron oxide, emergent contaminants, AOTS intensification

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Authors: Antonella Falanga, Armando Cartenì

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"Big data" refers to extremely vast and complex sets of data, encompassing extraordinarily large and intricate datasets that require specific tools for meaningful analysis and processing. These datasets can stem from diverse origins like sensors, mobile devices, online transactions, social media platforms, and more. The utilization of big data is pivotal, offering the chance to leverage vast information for substantial advantages across diverse fields, thereby enhancing comprehension, decision-making, efficiency, and fostering innovation in various domains. Big data, distinguished by its remarkable attributes of enormous volume, high velocity, diverse variety, and significant value, represent a transformative force reshaping the industry worldwide. Their pervasive impact continues to unlock new possibilities, driving innovation and advancements in technology, decision-making processes, and societal progress in an increasingly data-centric world. The use of these technologies is becoming more widespread, facilitating and accelerating operations that were once much more complicated. In particular, big data impacts across multiple sectors such as business and commerce, healthcare and science, finance, education, geography, agriculture, media and entertainment and also mobility and logistics. Within the transportation sector, which is the focus of this study, big data applications encompass a wide variety, spanning across optimization in vehicle routing, real-time traffic management and monitoring, logistics efficiency, reduction of travel times and congestion, enhancement of the overall transportation systems, but also mitigation of pollutant emissions contributing to environmental sustainability. Meanwhile, in public administration and the development of smart cities, big data aids in improving public services, urban planning, and decision-making processes, leading to more efficient and sustainable urban environments. Access to vast data reservoirs enables deeper insights, revealing hidden patterns and facilitating more precise and timely decision-making. Additionally, advancements in cloud computing and artificial intelligence (AI) have further amplified the potential of big data, enabling more sophisticated and comprehensive analyses. Certainly, utilizing big data presents various advantages but also entails several challenges regarding data privacy and security, ensuring data quality, managing and storing large volumes of data effectively, integrating data from diverse sources, the need for specialized skills to interpret analysis results, ethical considerations in data use, and evaluating costs against benefits. Addressing these difficulties requires well-structured strategies and policies to balance the benefits of big data with privacy, security, and efficient data management concerns. Building upon these premises, the current research investigates the efficacy and influence of big data by conducting an overview of the primary and recent implementations of big data in transportation systems. Overall, this research allows us to conclude that big data better provide to enhance rational decision-making for mobility choices and is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, public transport, sustainable mobility, transport demand, transportation planning

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Authors: Fani Sakellariadou, Danae Antivachis

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Purpose of this paper is to evaluate the environmental status of a coastal Mediterranean lake, named Koumoundourou, located in the northeastern coast of Elefsis Bay, in the western region of Attiki in Greece, 15 km far from Athens. It is preserved from ancient times having an important archaeological interest. Koumoundourou lake is also considered as a valuable wetland accommodating an abundant flora and fauna, with a variety of bird species including a few world’s threatened ones. Furthermore, it is a heavily modified lake, affected by various anthropogenic pollutant sources which provide industrial, urban and agricultural contaminants. The adjacent oil refineries and the military depot are the major pollution providers furnishing with crude oil spills and leaks. Moreover, the lake accepts a quantity of groundwater leachates from the major landfill of Athens. The environmental status of the lake results from the intensive land uses combined with the permeable lithology of the surrounding area and the existence of karstic springs which discharge calcareous mountains. Sediment samples were collected along the shoreline of the lake using a Van Veen grab stainless steel sampler. They were studied for the determination of the total metal content and the metal fractionation in geochemical phases as well as the characterization of the dissolved organic matter (DOM). These constituents have a significant role in the ecological consideration of the lake. Metals may be responsible for harmful environmental impacts. The metal partitioning offers comprehensive information for the origin, mode of occurrence, biological and physicochemical availability, mobilization and transport of metals. Moreover, DOM has a multifunctional importance interacting with inorganic and organic contaminants leading to biogeochemical and ecological effects. The samples were digested using microwave heating with a suitable laboratory microwave unit. For the total metal content, the samples were treated with a mixture of strong acids. Then, a sequential extraction procedure was applied for the removal of exchangeable, carbonate hosted, reducible, organic/sulphides and residual fractions. Metal content was determined by an ICP-MS (Perkin Elmer, ICP MASS Spectrophotometer NexION 350D). Furthermore, the DOM was removed via a gentle extraction procedure and then it was characterized by fluorescence spectroscopy using a Perkin-Elmer LS 55 luminescence spectrophotometer equipped with the WinLab 4.00.02 software for data processing (Agilent, Cary Eclipse Fluorescence). Mono dimensional emission, excitation, synchronous-scan excitation and total luminescence spectra were recorded for the classification of chromophoric units present in the aqueous extracts. Total metal concentrations were determined and compared with those of the Elefsis gulf sediments. Element partitioning showed the anthropogenic sources and the contaminant bioavailability. All fluorescence spectra, as well as humification indices, were evaluated in detail to find out the nature and origin of DOM. All the results were compared and interpreted to evaluate the environmental quality of Koumoundourou lake and the need for environmental management and protection.

Keywords: anthropogenic contaminant, dissolved organic matter, lake, metal, pollution

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Authors: Vishal Kumar, Soumitra Satapathi

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Föster Resonance Energy Transfer (FRET) is a powerful technique used to probe close-range molecular interactions. Physically, the FRET phenomenon manifests as a dipole–dipole interaction between closely juxtaposed fluorescent molecules (10–100 Å). Our effort is to employ this FRET technique to make a prototype device for highly sensitive detection of environment pollutant. Among the most common environmental pollutants, nitroaromatic compounds (NACs) are of particular interest because of their durability and toxicity. That’s why, sensitive and selective detection of small amounts of nitroaromatic explosives, in particular, 2,4,6-trinitrophenol (TNP), 2,4-dinitrotoluene (DNT) and 2,4,6-trinitrotoluene (TNT) has been a critical challenge due to the increasing threat of explosive-based terrorism and the need of environmental monitoring of drinking and waste water. In addition, the excessive utilization of TNP in several other areas such as burn ointment, pesticides, glass and the leather industry resulted in environmental accumulation, and is eventually contaminating the soil and aquatic systems. To the date, high number of elegant methods, including fluorimetry, gas chromatography, mass, ion-mobility and Raman spectrometry have been successfully applied for explosive detection. Among these efforts, fluorescence-quenching methods based on the mechanism of FRET show good assembly flexibility, high selectivity and sensitivity. Here, we report a FRET-based sensor system for the highly selective detection of NACs, such as TNP, DNT and TNT. The sensor system is composed of a copolymer Poly [(N,N-dimethylacrylamide)-co-(Boc-Trp-EMA)] (RP) bearing tryptophan derivative in the side chain as donor and dansyl tagged copolymer P(MMA-co-Dansyl-Ala-HEMA) (DCP) as an acceptor. Initially, the inherent fluorescence of RP copolymer is quenched by non-radiative energy transfer to DCP which only happens once the two molecules are within Förster critical distance (R0). The excellent spectral overlap (Jλ= 6.08×10¹⁴ nm⁴M⁻¹cm⁻¹) between donors’ (RP) emission profile and acceptors’ (DCP) absorption profile makes them an exciting and efficient FRET pair i.e. further confirmed by the high rate of energy transfer from RP to DCP i.e. 0.87 ns⁻¹ and lifetime measurement by time correlated single photon counting (TCSPC) to validate the 64% FRET efficiency. This FRET pair exhibited a specific fluorescence response to NACs such as DNT, TNT and TNP with 5.4, 2.3 and 0.4 µM LODs, respectively. The detection of NACs occurs with high sensitivity by photoluminescence quenching of FRET signal induced by photo-induced electron transfer (PET) from electron-rich FRET pair to electron-deficient NAC molecules. The estimated stern-volmer constant (KSV) values for DNT, TNT and TNP are 6.9 × 10³, 7.0 × 10³ and 1.6 × 104 M⁻¹, respectively. The mechanistic details of molecular interactions are established by time-resolved fluorescence, steady-state fluorescence and absorption spectroscopy confirmed that the sensing process is of mixed type, i.e. both dynamic and static quenching as lifetime of FRET system (0.73 ns) is reduced to 0.55, 0.57 and 0.61 ns DNT, TNT and TNP, respectively. In summary, the simplicity and sensitivity of this novel FRET sensor opens up the possibility of designing optical sensor of various NACs in one single platform for developing multimodal sensor for environmental monitoring and future field based study.

Keywords: FRET, nitroaromatic, stern-Volmer constant, tryptophan and dansyl tagged copolymer

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Authors: Cátia Gonçalves, Teresa Nunes, Inês Pina, Ana Vicente, C. Alves, Felix Charvet, Daniel Neves, A. Matos

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The production of charcoal relies on rudimentary technologies using traditional brick kilns. Charcoal is produced under pyrolysis conditions: breaking down the chemical structure of biomass under high temperature in the absence of air. The amount of the pyrolysis products (charcoal, pyroligneous extract, and flue gas) depends on various parameters, including temperature, time, pressure, kiln design, and wood characteristics like the moisture content. This activity is recognized for its inefficiency and high pollution levels, but it is poorly characterized. This activity is widely distributed and is a vital economic activity in certain regions of Portugal, playing a relevant role in the management of woody residues. The location of the units establishes the biomass used for charcoal production. The Portalegre district, in the Alto Alentejo region (Portugal), is a good example, essentially with rural characteristics, with a predominant farming, agricultural, and forestry profile, and with a significant charcoal production activity. In this district, a recent inventory identifies almost 50 charcoal production units, equivalent to more than 450 kilns, of which 80% appear to be in operation. A field campaign was designed with the objective of determining the composition of the emissions released during a charcoal production cycle. A total of 30 samples of particulate matter and 20 gas samples in Tedlar bags were collected. Particulate and gas samplings were performed in parallel, 2 in the morning and 2 in the afternoon, alternating the inlet heads (PM₁₀ and PM₂.₅), in the particulate sampler. The gas and particulate samples were collected in the plume as close as the emission chimney point. The biomass (dry basis) used in the carbonization process was a mixture of cork oak (77 wt.%), holm oak (7 wt.%), stumps (11 wt.%), and charred wood (5 wt.%) from previous carbonization processes. A cylindrical batch kiln (80 m³) with 4.5 m diameter and 5 m of height was used in this study. The composition of the gases was determined by gas chromatography, while the particulate samples (PM₁₀, PM₂.₅) were subjected to different analytical techniques (thermo-optical transmission technique, ion chromatography, HPAE-PAD, and GC-MS after solvent extraction) after prior gravimetric determination, to study their organic and inorganic constituents. The charcoal production cycle presents widely varying operating conditions, which will be reflected in the composition of gases and particles produced and emitted throughout the process. The concentration of PM₁₀ and PM₂.₅ in the plume was calculated, ranging between 0.003 and 0.293 g m⁻³, and 0.004 and 0.292 g m⁻³, respectively. Total carbon, inorganic ions, and sugars account, in average, for PM10 and PM₂.₅, 65 % and 56 %, 2.8 % and 2.3 %, 1.27 %, and 1.21 %, respectively. The organic fraction studied until now includes more than 30 aliphatic compounds and 20 PAHs. The emission factors of particulate matter to produce charcoal in the traditional kiln were 33 g/kg (wooddb) and 27 g/kg (wooddb) for PM₁₀ and PM₂.₅, respectively. With the data obtained in this study, it is possible to fill the lack of information about the environmental impact of the traditional charcoal production in Portugal. Acknowledgment: Authors thanks to FCT – Portuguese Science Foundation, I.P. and to Ministry of Science, Technology and Higher Education of Portugal for financial support within the scope of the project CHARCLEAN (PCIF/GVB/0179/2017) and CESAM (UIDP/50017/2020 + UIDB/50017/2020).

Keywords: brick kilns, charcoal, emission factors, PAHs, total carbon

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Authors: Piacentini Diego, Della Rovere Federica, Fattorini Laura, Lanni Francesca, Cittadini Martina, Altamura Maria Maddalena, Falasca Giuseppina

Abstract:

Plants have evolved sophisticated mechanisms to cope with environmental cues. Changes in intracellular content and distribution of phytohormones, such as the auxin indole-3-acetic acid (IAA), have been involved in morphogenic adaptation to environmental stresses. In addition to phytohormones, plants can rely on a plethora of small signal molecules able to promptly sense and transduce the stress signals, resulting in morpho/physiological responses thanks also to their capacity to modulate the levels/distribution/reception of most hormones. Among these signaling molecules, nitrogen monoxide (nitric oxide – NO) is a critical component in several plant acclimation strategies to both biotic and abiotic stresses. Depending on its levels, NO increases plant adaptation by enhancing the enzymatic or non-enzymatic antioxidant systems or by acting as a direct scavenger of reactive oxygen/nitrogen (ROS/RNS) species produced during the stress. In addition, exogenous applications of NO-specific donor compounds showed the involvement of the signal molecule in auxin metabolism, transport, and signaling, under both physiological and stress conditions. However, the complex mechanisms underlying NO action in interacting with phytohormones, such as auxins, during metal stress responses are still poorly understood and need to be better investigated. Emphasis must be placed on the response of the root system since it is the first plant organ system to be exposed to metal soil pollution. The monocot Oryza sativa L. (rice) has been chosen given its importance as a stable food for some 4 billion people worldwide. In addition, increasing evidence has shown that rice is often grown in contaminated paddy soils with high levels of heavy metal cadmium (Cd) and metalloid arsenic (As). The facility through which these metals are taken up by rice roots and transported to the aerial organs up to the edible caryopses makes rice one of the most relevant sources of these pollutants for humans. This study aimed to evaluate if NO has a mitigatory activity in the roots of rice seedlings against Cd or As toxicity and to understand if this activity requires interactions with auxin. Our results show that exogenous treatments with the NO-donor SNP alleviate the stress induced by Cd, but not by As, in in-vitro-grown rice seedlings through increased intracellular root NO levels. The damages induced by the pollutants include root growth inhibition, root histological alterations and ROS (H2O2, O2●ˉ), and RNS (ONOOˉ) production. Also, SNP treatments mitigate both the root increase in root IAA levels and the IAA alteration in distribution monitored by the OsDR5::GUS system due to the toxic metal exposure. Notably, the SNP-induced mitigation of the IAA homeostasis altered by the pollutants does not involve changes in the expression of OsYUCCA1 and ASA2 IAA-biosynthetic genes. Taken together, the results highlight a mitigating role of NO in the rice root system, which is pollutant-specific, and involves the interaction of the signal molecule with both IAA and brassinosteroids at different (i.e., transport, levels, distribution) and multiple levels (i.e., transcriptional/post-translational levels). The research is supported by Progetti Ateneo Sapienza University of Rome, grant number: RG120172B773D1FF

Keywords: arsenic, auxin, cadmium, nitric oxide, rice, root system

Procedia PDF Downloads 49

Authors: Julien Caudeville, Muriel Ismert

Abstract:

Analyzing the relationship between environment and health has become a major preoccupation for public health as evidenced by the emergence of the French national plans for health and environment. These plans have identified the following two priorities: (1) to identify and manage geographic areas, where hotspot exposures are suspected to generate a potential hazard to human health; (2) to reduce exposure inequalities. At a regional scale and fine resolution of exposure outcome prerequisite, environmental monitoring networks are not sufficient to characterize the multidimensionality of the exposure concept. In an attempt to increase representativeness of spatial exposure assessment approaches, risk composite indicators could be built using additional available databases and theoretical framework approaches to combine factor risks. To achieve those objectives, combining data process and transfer modeling with a spatial approach is a fundamental prerequisite that implies the need to first overcome different scientific limitations: to define interest variables and indicators that could be built to associate and describe the global source-effect chain; to link and process data from different sources and different spatial supports; to develop adapted methods in order to improve spatial data representativeness and resolution. A GIS-based modeling platform for quantifying human exposure to chemical substances (PLAINE: environmental inequalities analysis platform) was used to build health risk indicators within the Lorraine region (France). Those indicators combined chemical substances (in soil, air and water) and noise risk factors. Tools have been developed using modeling, spatial analysis and geostatistic methods to build and discretize interest variables from different supports and resolutions on a 1 km2 regular grid within the Lorraine region. By example, surface soil concentrations have been estimated by developing a Kriging method able to integrate surface and point spatial supports. Then, an exposure model developed by INERIS was used to assess the transfer from soil to individual exposure through ingestion pathways. We used distance from polluted soil site to build a proxy for contaminated site. Air indicator combined modeled concentrations and estimated emissions to take in account 30 polluants in the analysis. For water, drinking water concentrations were compared to drinking water standards to build a score spatialized using a distribution unit serve map. The Lden (day-evening-night) indicator was used to map noise around road infrastructures. Aggregation of the different factor risks was made using different methodologies to discuss weighting and aggregation procedures impact on the effectiveness of risk maps to take decisions for safeguarding citizen health. Results permit to identify pollutant sources, determinants of exposure, and potential hotspots areas. A diagnostic tool was developed for stakeholders to visualize and analyze the composite indicators in an operational and accurate manner. The designed support system will be used in many applications and contexts: (1) mapping environmental disparities throughout the Lorraine region; (2) identifying vulnerable population and determinants of exposure to set priorities and target for pollution prevention, regulation and remediation; (3) providing exposure database to quantify relationships between environmental indicators and cancer mortality data provided by French Regional Health Observatories.

Keywords: health risk, environment, composite indicator, hotspot areas

Procedia PDF Downloads 220