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In this work, we examine two modifications of fine-ground calcium carbonate material (GCC) in order to enhanced sorption of NO2 and subsequent reaction properties toward NO2-/NO3- formation by firstly exposing the GCC to supercritical (sc) CO2 in order to increase particle surface area, a choice specifically made to avoid altering the surface chemistry, and secondly considering the potential advantage of using a surface coupling agent toward NO2. The modification by the coupling agent amino silane (AMEO silane) was applied in a supercritical CO2-ethanol mixture. The samples were characterised before and after modification by field emission scanning electron microscopy (FESEM), specific surface area determination (BET nitrogen adsorption), ATR-FTIR spectroscopy and ion chromatography to reveal the effects of the surface modification(s) on the morphology, surface textural properties and sorption versus reaction properties with NO2. The performance of the treated sorbents for NO2 capture was evaluated at room temperature. Results show that reactivity of NO2 with GCC was observed to increase as a function of increased surface area resulting from scCO(2) exposure, but that the presence of AMEO silane on the surface, while enhancing initial adsorption of NO2 was seen subsequently to act to block reactivity. Thus, judicious use of coupling agent can provide desired rapid initial adsorption of the gas, but the goal of long-term CaCO3-consuming reactivity, so as to prolong the uptake of NO2 beyond surface saturation alone, is achieved by increasing surface area while retaining chemical-free exposed CaCO3 surface.

In this work, we examine two modifications of fine-ground calcium carbonate material (GCC) in order to enhanced sorption of NO2 and subsequent reaction properties toward NO2-/NO3- formation by firstly exposing the GCC to supercritical (sc) CO2 in order to increase particle surface area, a choice specifically made to avoid altering the surface chemistry, and secondly considering the potential advantage of using a surface coupling agent toward NO2. The modification by the coupling agent amino silane (AMEO silane) was applied in a supercritical CO2-ethanol mixture. The samples were characterised before and after modification by field emission scanning electron microscopy (FESEM), specific surface area determination (BET nitrogen adsorption), ATR-FTIR spectroscopy and ion chromatography to reveal the effects of the surface modification(s) on the morphology, surface textural properties and sorption versus reaction properties with NO2. The performance of the treated sorbents for NO2 capture was evaluated at room temperature. Results show that reactivity of NO2 with GCC was observed to increase as a function of increased surface area resulting from scCO(2) exposure, but that the presence of AMEO silane on the surface, while enhancing initial adsorption of NO2 was seen subsequently to act to block reactivity. Thus, judicious use of coupling agent can provide desired rapid initial adsorption of the gas, but the goal of long-term CaCO3-consuming reactivity, so as to prolong the uptake of NO2 beyond surface saturation alone, is achieved by increasing surface area while retaining chemical-free exposed CaCO3 surface.

In this work, we examine two modifications of fine-ground calcium carbonate material (GCC) in order to enhanced sorption of NO2 and subsequent reaction properties toward NO2-/NO3- formation by firstly exposing the GCC to supercritical (sc) CO2 in order to increase particle surface area, a choice specifically made to avoid altering the surface chemistry, and secondly considering the potential advantage of using a surface coupling agent toward NO2. The modification by the coupling agent amino silane (AMEO silane) was applied in a supercritical CO2-ethanol mixture. The samples were characterised before and after modification by field emission scanning electron microscopy (FESEM), specific surface area determination (BET nitrogen adsorption), ATR-FTIR spectroscopy and ion chromatography to reveal the effects of the surface modification(s) on the morphology, surface textural properties and sorption versus reaction properties with NO2. The performance of the treated sorbents for NO2 capture was evaluated at room temperature. Results show that reactivity of NO2 with GCC was observed to increase as a function of increased surface area resulting from scCO(2) exposure, but that the presence of AMEO silane on the surface, while enhancing initial adsorption of NO2 was seen subsequently to act to block reactivity. Thus, judicious use of coupling agent can provide desired rapid initial adsorption of the gas, but the goal of long-term CaCO3-consuming reactivity, so as to prolong the uptake of NO2 beyond surface saturation alone, is achieved by increasing surface area while retaining chemical-free exposed CaCO3 surface.

According to recent research, even low levels of environmental chemicals, particularly heavy metals, can considerably disrupt placental homeostasis. This review aims to explore the profile of non-essential trace metals in placental tissues across the globe and to specify trace metal(s) that can be candidates for impaired placental health. Accordingly, we conducted an extensive survey on relevant databases of peer-reviewed papers published in the last two decades. Among a considerable number of non-essential trace metals, arsenic (As), lead (Pb), cadmium (Cd), and mercury (Hg) were identified as the most detrimental to placental health. Comparative analysis showed remarkable differences in placental levels of these trace metals worldwide. Based on current data reported across the globe, a median (min–max) range from 0.55 to 15 ng/g for placental As levels could be deemed safe. The placental Cd and Pb levels were markedly higher in smokers than in non-smokers. Occupationally exposed pregnant women had several orders of magnitude higher Cd, Pb, and Hg levels in placental tissues than non-occupationally exposed women. Also, we concluded that even low-level exposure to As, Cd, Pb, and Hg could be deleterious to proper fetal development. This review implies the need to reduce exposure to non-essential trace metals to preserve placental health and prevent numerous poor pregnancy outcomes. Overall, the information presented is expected to help plan future fundamental and applied investigations on the placental toxicity of As, Cd, Pb, and Hg. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

According to recent research, even low levels of environmental chemicals, particularly heavy metals, can considerably disrupt placental homeostasis. This review aims to explore the profile of non-essential trace metals in placental tissues across the globe and to specify trace metal(s) that can be candidates for impaired placental health. Accordingly, we conducted an extensive survey on relevant databases of peer-reviewed papers published in the last two decades. Among a considerable number of non-essential trace metals, arsenic (As), lead (Pb), cadmium (Cd), and mercury (Hg) were identified as the most detrimental to placental health. Comparative analysis showed remarkable differences in placental levels of these trace metals worldwide. Based on current data reported across the globe, a median (min–max) range from 0.55 to 15 ng/g for placental As levels could be deemed safe. The placental Cd and Pb levels were markedly higher in smokers than in non-smokers. Occupationally exposed pregnant women had several orders of magnitude higher Cd, Pb, and Hg levels in placental tissues than non-occupationally exposed women. Also, we concluded that even low-level exposure to As, Cd, Pb, and Hg could be deleterious to proper fetal development. This review implies the need to reduce exposure to non-essential trace metals to preserve placental health and prevent numerous poor pregnancy outcomes. Overall, the information presented is expected to help plan future fundamental and applied investigations on the placental toxicity of As, Cd, Pb, and Hg. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

According to recent research, even low levels of environmental chemicals, particularly heavy metals, can considerably disrupt placental homeostasis. This review aims to explore the profile of non-essential trace metals in placental tissues across the globe and to specify trace metal(s) that can be candidates for impaired placental health. Accordingly, we conducted an extensive survey on relevant databases of peer-reviewed papers published in the last two decades. Among a considerable number of non-essential trace metals, arsenic (As), lead (Pb), cadmium (Cd), and mercury (Hg) were identified as the most detrimental to placental health. Comparative analysis showed remarkable differences in placental levels of these trace metals worldwide. Based on current data reported across the globe, a median (min–max) range from 0.55 to 15 ng/g for placental As levels could be deemed safe. The placental Cd and Pb levels were markedly higher in smokers than in non-smokers. Occupationally exposed pregnant women had several orders of magnitude higher Cd, Pb, and Hg levels in placental tissues than non-occupationally exposed women. Also, we concluded that even low-level exposure to As, Cd, Pb, and Hg could be deleterious to proper fetal development. This review implies the need to reduce exposure to non-essential trace metals to preserve placental health and prevent numerous poor pregnancy outcomes. Overall, the information presented is expected to help plan future fundamental and applied investigations on the placental toxicity of As, Cd, Pb, and Hg. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

According to recent research, even low levels of environmental chemicals, particularly heavy metals, can considerably disrupt placental homeostasis. This review aims to explore the profile of non-essential trace metals in placental tissues across the globe and to specify trace metal(s) that can be candidates for impaired placental health. Accordingly, we conducted an extensive survey on relevant databases of peer-reviewed papers published in the last two decades. Among a considerable number of non-essential trace metals, arsenic (As), lead (Pb), cadmium (Cd), and mercury (Hg) were identified as the most detrimental to placental health. Comparative analysis showed remarkable differences in placental levels of these trace metals worldwide. Based on current data reported across the globe, a median (min–max) range from 0.55 to 15 ng/g for placental As levels could be deemed safe. The placental Cd and Pb levels were markedly higher in smokers than in non-smokers. Occupationally exposed pregnant women had several orders of magnitude higher Cd, Pb, and Hg levels in placental tissues than non-occupationally exposed women. Also, we concluded that even low-level exposure to As, Cd, Pb, and Hg could be deleterious to proper fetal development. This review implies the need to reduce exposure to non-essential trace metals to preserve placental health and prevent numerous poor pregnancy outcomes. Overall, the information presented is expected to help plan future fundamental and applied investigations on the placental toxicity of As, Cd, Pb, and Hg. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

The paper briefly presents goals, activities, challenges, and outcomes of the NETCHEM project (http://www.netchem.ac.rs/) that was co-funded by the Erasmus+ Program of European Union (573885-EPP-1-2016-1-RS-EPPKA2- CBHE-JP). The project has been started in October 2016 and with extension lasted until April 2020. Western Balkan region has been targeted by upgrading capacities for education and research in environmental and food analysis in cooperation with partners from France, the UK, and Czech Republic. NETCHEM platform providing Web Accessed Remote Instrumental Analytical Laboratories (WARIAL) network, Database service and Open education system was created in order to improve the cooperation, educational, and research capacities of Higher Education Institutions involved, but also targeting whether audience not only from academic domain but from industry as well. The NETCHEM platform is free for access to public; thus, the external users to NETCHEM consortium can not only see its content but also actively participate, enter Database and WARIAL network, and upload their own educational/research material.

This paper presents the synthesis of a hybrid material through the use of natural pozzolan and titanium(IV) isopropoxide using the sol-gel method and its application in the photocatalytic hexavalent chromium reduction. The characterization data indicated a mesoporous material possessing a surface area of 271.7 m(2) g(-1). The morphology studies (SEM and TEM) showed nanosheet hybrid structures. The analysis of DRUV, FTIR, XRD, and Mossbauer spectroscopy provides a different electronic structure of the synthetized material when compared with the originals, proving the hybridization process between pozzolan and titanium(IV) isopropoxide. The photocatalytic reduction of Cr(VI) to Cr(III) using the hybrid material showed a better performance than conventional photocatalysts (precursor and TiO2-P25). Operational conditions such as chromium initial concentration (0.02-0.20 mM), solution pH (3-6), and type of scavenger (citric or tartaric acid) were evaluated in order to determine the best experimental conditions for the Cr(VI) photoreduction. At their optimum (catalyst load of 15 mg L-1, tartaric acid as scavenger, [scavenger](0)/[Cr(VI)](0) M ratio = 3:1, pH 3, and 25 degrees C), the total photoreduction of 0.20 mM Cr(VI) was achieved in 180 min. The novel hybrid materials synthesized from pozzolan and titanium(IV) isopropoxide showed to be a potential catalyst for the Cr(VI) reduction in aqueous solution.

The paper briefly presents goals, activities, challenges, and outcomes of the NETCHEM project (http://www.netchem.ac.rs/) that was co-funded by the Erasmus+ Program of European Union (573885-EPP-1-2016-1-RS-EPPKA2- CBHE-JP). The project has been started in October 2016 and with extension lasted until April 2020. Western Balkan region has been targeted by upgrading capacities for education and research in environmental and food analysis in cooperation with partners from France, the UK, and Czech Republic. NETCHEM platform providing Web Accessed Remote Instrumental Analytical Laboratories (WARIAL) network, Database service and Open education system was created in order to improve the cooperation, educational, and research capacities of Higher Education Institutions involved, but also targeting whether audience not only from academic domain but from industry as well. The NETCHEM platform is free for access to public; thus, the external users to NETCHEM consortium can not only see its content but also actively participate, enter Database and WARIAL network, and upload their own educational/research material.

The paper briefly presents goals, activities, challenges, and outcomes of the NETCHEM project (http://www.netchem.ac.rs/) that was co-funded by the Erasmus+ Program of European Union (573885-EPP-1-2016-1-RS-EPPKA2- CBHE-JP). The project has been started in October 2016 and with extension lasted until April 2020. Western Balkan region has been targeted by upgrading capacities for education and research in environmental and food analysis in cooperation with partners from France, the UK, and Czech Republic. NETCHEM platform providing Web Accessed Remote Instrumental Analytical Laboratories (WARIAL) network, Database service and Open education system was created in order to improve the cooperation, educational, and research capacities of Higher Education Institutions involved, but also targeting whether audience not only from academic domain but from industry as well. The NETCHEM platform is free for access to public; thus, the external users to NETCHEM consortium can not only see its content but also actively participate, enter Database and WARIAL network, and upload their own educational/research material.

The paper briefly presents goals, activities, challenges, and outcomes of the NETCHEM project (http://www.netchem.ac.rs/) that was co-funded by the Erasmus+ Program of European Union (573885-EPP-1-2016-1-RS-EPPKA2- CBHE-JP). The project has been started in October 2016 and with extension lasted until April 2020. Western Balkan region has been targeted by upgrading capacities for education and research in environmental and food analysis in cooperation with partners from France, the UK, and Czech Republic. NETCHEM platform providing Web Accessed Remote Instrumental Analytical Laboratories (WARIAL) network, Database service and Open education system was created in order to improve the cooperation, educational, and research capacities of Higher Education Institutions involved, but also targeting whether audience not only from academic domain but from industry as well. The NETCHEM platform is free for access to public; thus, the external users to NETCHEM consortium can not only see its content but also actively participate, enter Database and WARIAL network, and upload their own educational/research material.

The paper briefly presents goals, activities, challenges, and outcomes of the NETCHEM project (http://www.netchem.ac.rs/) that was co-funded by the Erasmus+ Program of European Union (573885-EPP-1-2016-1-RS-EPPKA2- CBHE-JP). The project has been started in October 2016 and with extension lasted until April 2020. Western Balkan region has been targeted by upgrading capacities for education and research in environmental and food analysis in cooperation with partners from France, the UK, and Czech Republic. NETCHEM platform providing Web Accessed Remote Instrumental Analytical Laboratories (WARIAL) network, Database service and Open education system was created in order to improve the cooperation, educational, and research capacities of Higher Education Institutions involved, but also targeting whether audience not only from academic domain but from industry as well. The NETCHEM platform is free for access to public; thus, the external users to NETCHEM consortium can not only see its content but also actively participate, enter Database and WARIAL network, and upload their own educational/research material.

The objective of the paper was to use transport model of selected pesticides (carbendazim, acetamiprid and imidacloprid) in determination of linear sorption coefficients in alluvial aquifer. For constructing transport model, results of a field experiment at the location of Kovin-Dubovac drainage system in Serbia were used in order to set hydraulic parameters (hydraulic conductivity, aquifer layer thickness of the observed area, effective porosity etc.). The field experiment consisted of a tracer test during which concentrations of non-reactive tracer (Cl−) and selected pesticides (carbendazim, acetamiprid and imidacloprid) were monitored. For better characterization of hydraulic parameters, a pumping test was conducted at the observed well and results were used in designing transport model. Simulation model was constructed with Lizza groundwater flow software and W.O.D.A. (Well Outline and Design Aid) solver. Obtained linear sorption coefficients in the sand and gravel water-bearing layer were 0.14 mL g−1 for carbendazim and 0.11 mL g−1 for acetamiprid and imidacloprid. Results from this study are a unique insight into mobility of observed pesticides in the alluvial groundwater in natural conditions and can be used in contamination assessment for drinking water wells.

Nowadays, the extensive use of pesticides in crops production puts a significant challenge to minimize its side effects along with safe production, storage, and after-use treatment. This paper reports results related to the emission of certain pesticide formulations through the PET containers, as well as, their mitigation to the PET containers during their storage. The influence of storage time on cypermethrin migration to and through the PET was studied in short-term Collaborative International Pesticides Analytical Council test lasting up to 30 days. The PET containers were filled with pure xylene and pesticide formulations, where the amount of active substance, cypermethrin (CY), varied from 5 to 20 wt%, while the amount of emulsifier was kept constant. The results indicate that pesticide formulations diffuse to PET containers with an average increase of its initial mass up to 1.5%. The most intensive diffusion is in the first 24 months of storage, after its rate significantly decreases. It should be noted that the diffusion studied pesticide formulations are also very dependent on CY concentration. Besides the migration to the PET containers, it was also found that pesticide formulation was emitted through the PET containers in the first 17 to 24 months of storage depending on CY concentration. Emission rates were also dependent on CY concentration and were in the range of 15.3 to 38.0 mg/month center dot container. The emission through the PETcontainers was successfully predicted using artificial neural networks with R-2 = 0.94 and the mean absolute percentage error (MAPE) of only 6.2% on testing.

Nowadays, the extensive use of pesticides in crops production puts a significant challenge to minimize its side effects along with safe production, storage, and after-use treatment. This paper reports results related to the emission of certain pesticide formulations through the PET containers, as well as, their mitigation to the PET containers during their storage. The influence of storage time on cypermethrin migration to and through the PET was studied in short-term Collaborative International Pesticides Analytical Council test lasting up to 30 days. The PET containers were filled with pure xylene and pesticide formulations, where the amount of active substance, cypermethrin (CY), varied from 5 to 20 wt%, while the amount of emulsifier was kept constant. The results indicate that pesticide formulations diffuse to PET containers with an average increase of its initial mass up to 1.5%. The most intensive diffusion is in the first 24 months of storage, after its rate significantly decreases. It should be noted that the diffusion studied pesticide formulations are also very dependent on CY concentration. Besides the migration to the PET containers, it was also found that pesticide formulation was emitted through the PET containers in the first 17 to 24 months of storage depending on CY concentration. Emission rates were also dependent on CY concentration and were in the range of 15.3 to 38.0 mg/month center dot container. The emission through the PETcontainers was successfully predicted using artificial neural networks with R-2 = 0.94 and the mean absolute percentage error (MAPE) of only 6.2% on testing.

Heavy metals such as lead are well known to cause harmful health effects. Especially children are particularly susceptible to increased levels of lead in their blood. It is also a fact that lead concentration is increasing in the environment due to increased anthropogenic activity. The risk of heavy metal contamination is pronounced in the environment adjacent to large industrial complexes. In a combined case study, the environmental pollution by heavy metals was related to children's health in the vicinity of an industrial area located 4 km south-east from Bucharest about 2 km east from the nearest town-Pantelimon. This site includes companies processing different, nonferrous solid wastes for recovery of heavy metals and producing different nonferrous alloys and lead batteries. In this paper, mainly the results of environmental sampling and analyses are summarized.

Erworben im Rahmen der Schweizer Nationallizenzen (http://www.nationallizenzen.ch), Solid waste management (SWM) is a significant challenge for the Seychelles. Waste generation, fueled by economic development and tourism, increases steadily, while landfilling continues to be the main disposal path, thus exacerbating the island nation's specific weaknesses. Due to the small scale of the Seychelles economy, there is little capital available to stimulate innovations in SWM and generate the knowledge for setting priorities and guiding SWM action. Students from ETH Zurich and UniSey conducted a transdisciplinary case study (tdCS) to fill this knowledge gap and gain insights into the obstacles and opportunities related to sustainable SWM. The tdCS approach allowed students to gain comprehensive and in-depth knowledge about the SWM system required to set priorities for action and next steps. The government should streamline the different financial frameworks according to a clear principle (e.g., polluter pays principle). Specific biogenic waste streams represent a potential source of energy and fertilizers. Expanding the scope and densifying the network of collection points could help raise recycling rates of other waste fractions. Diverting biogenic waste and recycling more glass, metals, paper, and plastics would also significantly reduce landfilling rates. Regardless of future amounts of waste ending up on landfills, the latter must be reengineered before the surrounding environment suffers major adverse impacts. All these actions imply a government-driven approach which integrates the views of stakeholders and consumers alike.

This paper presents an application of experimental design for the optimization of artificial neural network (ANN) for the prediction of dissolved oxygen (DO) content in the Danube River. The aim of this research was to obtain a more reliable ANN model that uses fewer monitoring records, by simultaneous optimization of the following model parameters: number of monitoring sites, number of historical monitoring data (expressed in years), and number of input water quality parameters used. Box-Behnken three-factor at three levels experimental design was applied for simultaneous spatial, temporal, and input variables optimization of the ANN model. The prediction of DO was performed using a feed-forward back-propagation neural network (BPNN), while the selection of most important inputs was done off-model using multi-filter approach that combines a chi-square ranking in the first step with a correlation-based elimination in the second step. The contour plots of absolute and relative error response surfaces were utilized to determine the optimal values of design factors. From the contour plots, two BPNN models that cover entire Danube flow through Serbia are proposed: an upstream model (BPNN-UP) that covers 8 monitoring sites prior to Belgrade and uses 12 inputs measured in the 7-year period and a downstream model (BPNN-DOWN) which covers 9 monitoring sites and uses 11 input parameters measured in the 6-year period. The main difference between the two models is that BPNN-UP utilizes inputs such as BOD, P, and PO43-, which is in accordance with the fact that this model covers northern part of Serbia (Vojvodina Autonomous Province) which is well-known for agricultural production and extensive use of fertilizers. Both models have shown very good agreement between measured and predicted DO (with R-2 gt = 0.86) and demonstrated that they can effectively forecast DO content in the Danube River.

This paper presents an application of experimental design for the optimization of artificial neural network (ANN) for the prediction of dissolved oxygen (DO) content in the Danube River. The aim of this research was to obtain a more reliable ANN model that uses fewer monitoring records, by simultaneous optimization of the following model parameters: number of monitoring sites, number of historical monitoring data (expressed in years), and number of input water quality parameters used. Box-Behnken three-factor at three levels experimental design was applied for simultaneous spatial, temporal, and input variables optimization of the ANN model. The prediction of DO was performed using a feed-forward back-propagation neural network (BPNN), while the selection of most important inputs was done off-model using multi-filter approach that combines a chi-square ranking in the first step with a correlation-based elimination in the second step. The contour plots of absolute and relative error response surfaces were utilized to determine the optimal values of design factors. From the contour plots, two BPNN models that cover entire Danube flow through Serbia are proposed: an upstream model (BPNN-UP) that covers 8 monitoring sites prior to Belgrade and uses 12 inputs measured in the 7-year period and a downstream model (BPNN-DOWN) which covers 9 monitoring sites and uses 11 input parameters measured in the 6-year period. The main difference between the two models is that BPNN-UP utilizes inputs such as BOD, P, and PO43-, which is in accordance with the fact that this model covers northern part of Serbia (Vojvodina Autonomous Province) which is well-known for agricultural production and extensive use of fertilizers. Both models have shown very good agreement between measured and predicted DO (with R-2 gt = 0.86) and demonstrated that they can effectively forecast DO content in the Danube River.

Heavy metals such as lead are well known to cause harmful health effects. Especially children are particularly susceptible to increased levels of lead in their blood. It is also a fact that lead concentration is increasing in the environment due to increased anthropogenic activity. The risk of heavy metal contamination is pronounced in the environment adjacent to large industrial complexes. In a combined case study, the environmental pollution by heavy metals was related to children's health in the vicinity of an industrial area located 4 km south-east from Bucharest about 2 km east from the nearest town-Pantelimon. This site includes companies processing different, nonferrous solid wastes for recovery of heavy metals and producing different nonferrous alloys and lead batteries. In this paper, mainly the results of environmental sampling and analyses are summarized.

Erworben im Rahmen der Schweizer Nationallizenzen (http://www.nationallizenzen.ch), Solid waste management (SWM) is a significant challenge for the Seychelles. Waste generation, fueled by economic development and tourism, increases steadily, while landfilling continues to be the main disposal path, thus exacerbating the island nation's specific weaknesses. Due to the small scale of the Seychelles economy, there is little capital available to stimulate innovations in SWM and generate the knowledge for setting priorities and guiding SWM action. Students from ETH Zurich and UniSey conducted a transdisciplinary case study (tdCS) to fill this knowledge gap and gain insights into the obstacles and opportunities related to sustainable SWM. The tdCS approach allowed students to gain comprehensive and in-depth knowledge about the SWM system required to set priorities for action and next steps. The government should streamline the different financial frameworks according to a clear principle (e.g., polluter pays principle). Specific biogenic waste streams represent a potential source of energy and fertilizers. Expanding the scope and densifying the network of collection points could help raise recycling rates of other waste fractions. Diverting biogenic waste and recycling more glass, metals, paper, and plastics would also significantly reduce landfilling rates. Regardless of future amounts of waste ending up on landfills, the latter must be reengineered before the surrounding environment suffers major adverse impacts. All these actions imply a government-driven approach which integrates the views of stakeholders and consumers alike.

This paper presents the development of a general regression neural network (GRNN) model for the prediction of annual municipal solid waste (MSW) generation at the national level for 44 countries of different size, population and economic development level. Proper modelling of MSW generation is essential for the planning of MSW management system as well as for the simulation of various environmental impact scenarios. The main objective of this work was to examine the potential influence of economy crisis (global or local) on the forecast of MSW generation obtained by the GRNN model. The existence of the so-called structural breaks that occur because of the economic crisis in the studied period (2000-2012) for each country was determined and confirmed using the Chow test and Quandt-Andrews test. Two GRNN models, one which did not take into account the influence of the economic crisis (GRNN) and another one which did (SB-GRNN), were developed. The novelty of the applied method is that it uses broadly available social, economic and demographic indicators and indicators of sustainability, together with GRNN and structural break testing for the prediction of MSW generation at the national level. The obtained results demonstrate that the SB-GRNN model provide more accurate predictions than the model which neglected structural breaks, with a mean absolute percentage error (MAPE) of 4.0 % compared to 6.7 % generated by the GRNN model. The proposed model enhanced with structural breaks can be a viable alternative for a more accurate prediction of MSW generation at the national level, especially for developing countries for which a lack of MSW data is notable.

Modern, efficient and cost-effective approach to remediation of heavy metal-contaminated soil is based on the application of microorganisms. In this paper, four isolates from agricultural and urban contaminated soil showed abundant growth in the presence of copper(II) sulfate pentahydrate (CuSO4·5H2O) up to 2 mM. Selected yeasts were identified by molecular methods as Candida tropicalis (three isolates) and Schwanniomyces occidentalis (one isolate). C. tropicalis (4TD1101S) showed the highest percentage of bioaccumulation capabilities (94.37%), determined by the inductively coupled plasma optical emission spectrometry (ICP-OES). The Raman spectra of C. tropicalis (4TD1101S) analyzed in a medium with the addition of 2 mM CuSO4·5H2O showed certain increase in metallothionein production, which represents a specific response of the yeast species to the stress conditions. These results indicate that soil yeasts represent a potential for practical application in the bioremediation of contaminated environments.

This paper presents indoor radon concentrations and specific activities of natural radionuclides measured in soils of Kosovo and Metohija. The measurements of radon concentration were performed during two consecutive 6-month periods in two rooms of 63 houses using CR-39 detectors. The annual radon concentration ranged from 30 to 810 Bq m(-3) with the average value of 128 Bq m(-3). Almost 15% of the houses had radon concentration higher than 200 Bq m(-3). The difference between radon concentrations measured in the two 6-month periods was analyzed, showing, as expected, a slightly higher radon concentration in the winter period than in the summer period. The variation between different rooms of the same houses was also analyzed, showing that 20% of the dwellings had a significantly higher radon concentration ( GT 100 Bq m(-3)) in one room compared to the other (the coefficient of variation ranged up to 96%). The specific activities of natural radionuclides in the nearby soil were determined by gamma spectrometry. The estimated average value (and standard deviation) of Ra-226, Th-232, and K-40 specific activities were 32 (13), 35 (16), and 582 (159) Bq kg(-1), respectively. The correlation between indoor Rn-222 and Ra-226 content in soil was investigated. Only a weak correlation was found (Spearmans rho = 0.220) indicating that other factors might affect diffusion and accumulation of radon indoors, as confirmed also by the high variability between the rooms of the same houses.

In this paper, pristine and chemically treated multi-walled carbon nanotubes (MWCNTs) were employed as solid-phase extraction sorbents for the isolation and enrichment of multi-class pharmaceuticals from the surface water and groundwater, prior to liquid chromatography-tandem mass spectrometry analysis. Thirteen pharmaceuticals that belong to different therapeutical classes (erythromycin, azithromycin, sulfamethoxazole, diazepam, lorazepam, carbamazepine, metoprolol, bisoprolol, enalapril, cilazapril, simvastatin, clopidogrel, diclofenac) and two metabolites of metamizole (4-acetylaminoantipyrine and 4-formylaminoantipyrine) were selected for this study. The influence of chemical treatment on MWCNT surface characteristics and extraction efficiency was studied, and it was shown that HCl treatment of MWCNT leads to a decrease in the amount of surface oxygen groups and at the same time favorably affects the efficiency toward extraction of selected pharmaceuticals. After the optimization of the SPE procedure, the following conditions were chosen: 50 mg of HCl-treated MCWNT as a sorbent, 100 mL of water sample at pH 6, and 15 mL of the methanol-dichloromethane mixture (1:1, v/v) as eluent. Under optimal conditions, high recoveries (79-119%), as well as low detection (0.2 to 103 ng L-1) and quantitation (0.5-345 ng L-1) limits, were obtained. The optimized method was applied to the analysis of five surface water and two groundwater samples, and three pharmaceuticals were detected, the antiepileptic drug carbamazepine and two metabolites of antipyretic metamizole.

This paper presents the development of a general regression neural network (GRNN) model for the prediction of annual municipal solid waste (MSW) generation at the national level for 44 countries of different size, population and economic development level. Proper modelling of MSW generation is essential for the planning of MSW management system as well as for the simulation of various environmental impact scenarios. The main objective of this work was to examine the potential influence of economy crisis (global or local) on the forecast of MSW generation obtained by the GRNN model. The existence of the so-called structural breaks that occur because of the economic crisis in the studied period (2000-2012) for each country was determined and confirmed using the Chow test and Quandt-Andrews test. Two GRNN models, one which did not take into account the influence of the economic crisis (GRNN) and another one which did (SB-GRNN), were developed. The novelty of the applied method is that it uses broadly available social, economic and demographic indicators and indicators of sustainability, together with GRNN and structural break testing for the prediction of MSW generation at the national level. The obtained results demonstrate that the SB-GRNN model provide more accurate predictions than the model which neglected structural breaks, with a mean absolute percentage error (MAPE) of 4.0 % compared to 6.7 % generated by the GRNN model. The proposed model enhanced with structural breaks can be a viable alternative for a more accurate prediction of MSW generation at the national level, especially for developing countries for which a lack of MSW data is notable.

In this paper, pristine and chemically treated multi-walled carbon nanotubes (MWCNTs) were employed as solid-phase extraction sorbents for the isolation and enrichment of multi-class pharmaceuticals from the surface water and groundwater, prior to liquid chromatography-tandem mass spectrometry analysis. Thirteen pharmaceuticals that belong to different therapeutical classes (erythromycin, azithromycin, sulfamethoxazole, diazepam, lorazepam, carbamazepine, metoprolol, bisoprolol, enalapril, cilazapril, simvastatin, clopidogrel, diclofenac) and two metabolites of metamizole (4-acetylaminoantipyrine and 4-formylaminoantipyrine) were selected for this study. The influence of chemical treatment on MWCNT surface characteristics and extraction efficiency was studied, and it was shown that HCl treatment of MWCNT leads to a decrease in the amount of surface oxygen groups and at the same time favorably affects the efficiency toward extraction of selected pharmaceuticals. After the optimization of the SPE procedure, the following conditions were chosen: 50 mg of HCl-treated MCWNT as a sorbent, 100 mL of water sample at pH 6, and 15 mL of the methanol-dichloromethane mixture (1:1, v/v) as eluent. Under optimal conditions, high recoveries (79-119%), as well as low detection (0.2 to 103 ng L-1) and quantitation (0.5-345 ng L-1) limits, were obtained. The optimized method was applied to the analysis of five surface water and two groundwater samples, and three pharmaceuticals were detected, the antiepileptic drug carbamazepine and two metabolites of antipyretic metamizole.

Modern, efficient, and cost-effective approach to remediation of heavy metal-contaminated soil is based on the application of microorganisms. In this paper, four isolates from agricultural and urban contaminated soil showed abundant growth in the presence of copper(II) sulfate pentahydrate (CuSO4 center dot 5H(2)O) up to 2 mM. Selected yeasts were identified by molecular methods as Candida tropicalis (three isolates) and Schwanniomyces occidentalis (one isolate). C. tropicalis (4TD1101S) showed the highest percentage of bioaccumulation capabilities (94.37%), determined by the inductively coupled plasma optical emission spectrometry (ICP-OES). The Raman spectra of C. tropicalis (4TD1101S) analyzed in a medium with the addition of 2 mM CuSO4 center dot 5H(2)O showed certain increase in metallothionein production, which represents a specific response of the yeast species to the stress conditions. These results indicate that soil yeasts represent a potential for practical application in the bioremediation of contaminated environments.

Modern, efficient, and cost-effective approach to remediation of heavy metal-contaminated soil is based on the application of microorganisms. In this paper, four isolates from agricultural and urban contaminated soil showed abundant growth in the presence of copper(II) sulfate pentahydrate (CuSO4 center dot 5H(2)O) up to 2 mM. Selected yeasts were identified by molecular methods as Candida tropicalis (three isolates) and Schwanniomyces occidentalis (one isolate). C. tropicalis (4TD1101S) showed the highest percentage of bioaccumulation capabilities (94.37%), determined by the inductively coupled plasma optical emission spectrometry (ICP-OES). The Raman spectra of C. tropicalis (4TD1101S) analyzed in a medium with the addition of 2 mM CuSO4 center dot 5H(2)O showed certain increase in metallothionein production, which represents a specific response of the yeast species to the stress conditions. These results indicate that soil yeasts represent a potential for practical application in the bioremediation of contaminated environments.

This paper presents the development of a general regression neural network (GRNN) model for the prediction of annual municipal solid waste (MSW) generation at the national level for 44 countries of different size, population and economic development level. Proper modelling of MSW generation is essential for the planning of MSW management system as well as for the simulation of various environmental impact scenarios. The main objective of this work was to examine the potential influence of economy crisis (global or local) on the forecast of MSW generation obtained by the GRNN model. The existence of the so-called structural breaks that occur because of the economic crisis in the studied period (2000-2012) for each country was determined and confirmed using the Chow test and Quandt-Andrews test. Two GRNN models, one which did not take into account the influence of the economic crisis (GRNN) and another one which did (SB-GRNN), were developed. The novelty of the applied method is that it uses broadly available social, economic and demographic indicators and indicators of sustainability, together with GRNN and structural break testing for the prediction of MSW generation at the national level. The obtained results demonstrate that the SB-GRNN model provide more accurate predictions than the model which neglected structural breaks, with a mean absolute percentage error (MAPE) of 4.0 % compared to 6.7 % generated by the GRNN model. The proposed model enhanced with structural breaks can be a viable alternative for a more accurate prediction of MSW generation at the national level, especially for developing countries for which a lack of MSW data is notable.

In this paper, pristine and chemically treated multi-walled carbon nanotubes (MWCNTs) were employed as solid-phase extraction sorbents for the isolation and enrichment of multi-class pharmaceuticals from the surface water and groundwater, prior to liquid chromatography-tandem mass spectrometry analysis. Thirteen pharmaceuticals that belong to different therapeutical classes (erythromycin, azithromycin, sulfamethoxazole, diazepam, lorazepam, carbamazepine, metoprolol, bisoprolol, enalapril, cilazapril, simvastatin, clopidogrel, diclofenac) and two metabolites of metamizole (4-acetylaminoantipyrine and 4-formylaminoantipyrine) were selected for this study. The influence of chemical treatment on MWCNT surface characteristics and extraction efficiency was studied, and it was shown that HCl treatment of MWCNT leads to a decrease in the amount of surface oxygen groups and at the same time favorably affects the efficiency toward extraction of selected pharmaceuticals. After the optimization of the SPE procedure, the following conditions were chosen: 50 mg of HCl-treated MCWNT as a sorbent, 100 mL of water sample at pH 6, and 15 mL of the methanol-dichloromethane mixture (1:1, v/v) as eluent. Under optimal conditions, high recoveries (79-119%), as well as low detection (0.2 to 103 ng L-1) and quantitation (0.5-345 ng L-1) limits, were obtained. The optimized method was applied to the analysis of five surface water and two groundwater samples, and three pharmaceuticals were detected, the antiepileptic drug carbamazepine and two metabolites of antipyretic metamizole.

This paper presents indoor radon concentrations and specific activities of natural radionuclides measured in soils of Kosovo and Metohija. The measurements of radon concentration were performed during two consecutive 6-month periods in two rooms of 63 houses using CR-39 detectors. The annual radon concentration ranged from 30 to 810 Bq m(-3) with the average value of 128 Bq m(-3). Almost 15% of the houses had radon concentration higher than 200 Bq m(-3). The difference between radon concentrations measured in the two 6-month periods was analyzed, showing, as expected, a slightly higher radon concentration in the winter period than in the summer period. The variation between different rooms of the same houses was also analyzed, showing that 20% of the dwellings had a significantly higher radon concentration ( GT 100 Bq m(-3)) in one room compared to the other (the coefficient of variation ranged up to 96%). The specific activities of natural radionuclides in the nearby soil were determined by gamma spectrometry. The estimated average value (and standard deviation) of Ra-226, Th-232, and K-40 specific activities were 32 (13), 35 (16), and 582 (159) Bq kg(-1), respectively. The correlation between indoor Rn-222 and Ra-226 content in soil was investigated. Only a weak correlation was found (Spearmans rho = 0.220) indicating that other factors might affect diffusion and accumulation of radon indoors, as confirmed also by the high variability between the rooms of the same houses.

In this paper, pristine and chemically treated multi-walled carbon nanotubes (MWCNTs) were employed as solid-phase extraction sorbents for the isolation and enrichment of multi-class pharmaceuticals from the surface water and groundwater, prior to liquid chromatography-tandem mass spectrometry analysis. Thirteen pharmaceuticals that belong to different therapeutical classes (erythromycin, azithromycin, sulfamethoxazole, diazepam, lorazepam, carbamazepine, metoprolol, bisoprolol, enalapril, cilazapril, simvastatin, clopidogrel, diclofenac) and two metabolites of metamizole (4-acetylaminoantipyrine and 4-formylaminoantipyrine) were selected for this study. The influence of chemical treatment on MWCNT surface characteristics and extraction efficiency was studied, and it was shown that HCl treatment of MWCNT leads to a decrease in the amount of surface oxygen groups and at the same time favorably affects the efficiency toward extraction of selected pharmaceuticals. After the optimization of the SPE procedure, the following conditions were chosen: 50 mg of HCl-treated MCWNT as a sorbent, 100 mL of water sample at pH 6, and 15 mL of the methanol-dichloromethane mixture (1:1, v/v) as eluent. Under optimal conditions, high recoveries (79-119%), as well as low detection (0.2 to 103 ng L-1) and quantitation (0.5-345 ng L-1) limits, were obtained. The optimized method was applied to the analysis of five surface water and two groundwater samples, and three pharmaceuticals were detected, the antiepileptic drug carbamazepine and two metabolites of antipyretic metamizole.

n The present paper focuses on the determination of radiological characteristics of cultivated chernozem soil and crops from long-term field experiments, taking into account the importance of distribution and transfer of radionuclides in the soil-plant system, especially in agricultural cropland. The investigation was performed on the experimental fields where maize, winter wheat, and rapeseed were cultivated. Analysis of radioactivity included determination of the gross alpha and beta activity as a screening method, as well as the activities of the following radiouclides: natural (Pb-210, U-235, U-238, Ra-226, Th-232, K-40, Be-7) and artificial (Sr-90 and Cs-137). The activities of natural and artificial (Cs-137) radionuclides were determined by gamma spectrometry, while the artificial radionuclide Sr-90 was determined by a radiochemical analytical method. Based on the obtained results for the specific activity of K-40, Cs-137, and Sr-90, accumulation factors for these radionuclides were calculated in order to estimate transfer of radionuclides from soil to crops. The results of performed analyses showed that there is no increase of radioactivity that could endanger the food production through the grown crops.

In this paper, the data for ten water quality variables collected during 2009 at 75 monitoring sites along the river network of Serbia are considered. The results are alarming because 48 % of the studied sites were contaminated by Ni, Mn, Pb, As, and nutrients, which are key factors impairing the water quality of the rivers in Serbia. Special attention should be paid to Zn and Cu, listed in the priority toxic pollutants of US EPA for aquatic life protection. The employed Q-model cluster analysis grouped the data into three major pollution zones (low, moderate, and high). Most sites classified as "low pollution zones" (LP) were in the main rivers, whereas those classified as "moderate and high pollution zones" (MP and HP, respectively) were in the large and small tributaries/hydro-system. Principal component analysis/factor analysis (PCA/FA) showed that the dissolved metals and nutrients in the Serbian rivers varied depending on the river, the heterogeneity of the anthropogenic activities in the basins (influenced primarily by industrial wastewater, agricultural activities, and urban runoff pollution), and natural environmental variability, such as geological characteristics. In LP dominated non-point source pollution, such as agricultural and urban runoff, whereas mixed source pollution dominated in the MP and HP zones. These results provide information to be used for developing better pollution control strategies for the river network of Serbia.

This paper describes the development of an artificial neural network (ANN) model based on economical and sustainability indicators for the prediction of annual non-methane volatile organic compounds (NMVOCs) emissions in China for the period 2005-2011 and its comparison with inventory emission factor models. The NMVOCs emissions in China were estimated using ANN model which was created using available data for nine European countries, which NMVOC emission per capita approximately correspond to the Chinese emissions, for the period 2004-2012. The forward input selection strategy was used to compare the significance of particular inputs for the prediction of NMVOC emissions in the nine selected EU countries and China. The final ANN model was trained using only five input variables, and it has demonstrated similar accuracy in predicting NMVOC emissions for the selected EU countries that were used for the development of the model and then for China for which the input dataset was previously unknown to the ANN model. The obtained mean absolute percentage error (MAPE) values were 8 % for EU countries and 5 % for China. Also, the temporal trend of NMVOC emissions predicted in this study is generally consistent with the trend obtained using inventory emission models. The proposed ANN approach can represent a viable alternative for the prediction of NMVOC emissions at the national level, in particular for developing countries which are usually lacking emission data.

In the present work, the sorption ability of 17 pharmaceutical compounds, two metabolites, and 15 pesticides (34 target compounds in total) onto four different river sediments was investigated separately. Selected compounds present the most frequently prescribed pharmaceuticals in human and animal medicine and the most frequently used pesticides in agriculture. Their presence into the surface, ground, and waste waters was confirmed into the numerous papers in literature, as well as their presence into the river sediments (for some of them). However, investigations of their sorption onto the river sediments, as major natural protection from potential pollution of ground water by them is missing. Sorption in this study was investigated onto river sediments taken from rivers in the Republic of Serbia, where only less than 10 % of total generated waste water passes through mainly basic treatment processes. Experiments were based on batch equilibrium procedures and obtained solutions were analyzed by previously developed and validated sensitive high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) analytical methods. All results were modeled by Freundlich isotherms. Obtained results have shown that Kf coefficient values are in correlation with organic carbon content. Kd sorption coefficient values were relatively low and ranged in wide ranges for almost all compounds and sediments. That implicates on the conclusion that capacities of the investigated sorbents are not large for those compounds.

n The present paper focuses on the determination of radiological characteristics of cultivated chernozem soil and crops from long-term field experiments, taking into account the importance of distribution and transfer of radionuclides in the soil-plant system, especially in agricultural cropland. The investigation was performed on the experimental fields where maize, winter wheat, and rapeseed were cultivated. Analysis of radioactivity included determination of the gross alpha and beta activity as a screening method, as well as the activities of the following radiouclides: natural (Pb-210, U-235, U-238, Ra-226, Th-232, K-40, Be-7) and artificial (Sr-90 and Cs-137). The activities of natural and artificial (Cs-137) radionuclides were determined by gamma spectrometry, while the artificial radionuclide Sr-90 was determined by a radiochemical analytical method. Based on the obtained results for the specific activity of K-40, Cs-137, and Sr-90, accumulation factors for these radionuclides were calculated in order to estimate transfer of radionuclides from soil to crops. The results of performed analyses showed that there is no increase of radioactivity that could endanger the food production through the grown crops.

n The present paper focuses on the determination of radiological characteristics of cultivated chernozem soil and crops from long-term field experiments, taking into account the importance of distribution and transfer of radionuclides in the soil-plant system, especially in agricultural cropland. The investigation was performed on the experimental fields where maize, winter wheat, and rapeseed were cultivated. Analysis of radioactivity included determination of the gross alpha and beta activity as a screening method, as well as the activities of the following radiouclides: natural (Pb-210, U-235, U-238, Ra-226, Th-232, K-40, Be-7) and artificial (Sr-90 and Cs-137). The activities of natural and artificial (Cs-137) radionuclides were determined by gamma spectrometry, while the artificial radionuclide Sr-90 was determined by a radiochemical analytical method. Based on the obtained results for the specific activity of K-40, Cs-137, and Sr-90, accumulation factors for these radionuclides were calculated in order to estimate transfer of radionuclides from soil to crops. The results of performed analyses showed that there is no increase of radioactivity that could endanger the food production through the grown crops.

In the present work, the sorption ability of 17 pharmaceutical compounds, two metabolites, and 15 pesticides (34 target compounds in total) onto four different river sediments was investigated separately. Selected compounds present the most frequently prescribed pharmaceuticals in human and animal medicine and the most frequently used pesticides in agriculture. Their presence into the surface, ground, and waste waters was confirmed into the numerous papers in literature, as well as their presence into the river sediments (for some of them). However, investigations of their sorption onto the river sediments, as major natural protection from potential pollution of ground water by them is missing. Sorption in this study was investigated onto river sediments taken from rivers in the Republic of Serbia, where only less than 10 % of total generated waste water passes through mainly basic treatment processes. Experiments were based on batch equilibrium procedures and obtained solutions were analyzed by previously developed and validated sensitive high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) analytical methods. All results were modeled by Freundlich isotherms. Obtained results have shown that Kf coefficient values are in correlation with organic carbon content. Kd sorption coefficient values were relatively low and ranged in wide ranges for almost all compounds and sediments. That implicates on the conclusion that capacities of the investigated sorbents are not large for those compounds.

This paper describes the development of an artificial neural network (ANN) model based on economical and sustainability indicators for the prediction of annual non-methane volatile organic compounds (NMVOCs) emissions in China for the period 2005-2011 and its comparison with inventory emission factor models. The NMVOCs emissions in China were estimated using ANN model which was created using available data for nine European countries, which NMVOC emission per capita approximately correspond to the Chinese emissions, for the period 2004-2012. The forward input selection strategy was used to compare the significance of particular inputs for the prediction of NMVOC emissions in the nine selected EU countries and China. The final ANN model was trained using only five input variables, and it has demonstrated similar accuracy in predicting NMVOC emissions for the selected EU countries that were used for the development of the model and then for China for which the input dataset was previously unknown to the ANN model. The obtained mean absolute percentage error (MAPE) values were 8 % for EU countries and 5 % for China. Also, the temporal trend of NMVOC emissions predicted in this study is generally consistent with the trend obtained using inventory emission models. The proposed ANN approach can represent a viable alternative for the prediction of NMVOC emissions at the national level, in particular for developing countries which are usually lacking emission data.

In this paper, the data for ten water quality variables collected during 2009 at 75 monitoring sites along the river network of Serbia are considered. The results are alarming because 48 % of the studied sites were contaminated by Ni, Mn, Pb, As, and nutrients, which are key factors impairing the water quality of the rivers in Serbia. Special attention should be paid to Zn and Cu, listed in the priority toxic pollutants of US EPA for aquatic life protection. The employed Q-model cluster analysis grouped the data into three major pollution zones (low, moderate, and high). Most sites classified as "low pollution zones" (LP) were in the main rivers, whereas those classified as "moderate and high pollution zones" (MP and HP, respectively) were in the large and small tributaries/hydro-system. Principal component analysis/factor analysis (PCA/FA) showed that the dissolved metals and nutrients in the Serbian rivers varied depending on the river, the heterogeneity of the anthropogenic activities in the basins (influenced primarily by industrial wastewater, agricultural activities, and urban runoff pollution), and natural environmental variability, such as geological characteristics. In LP dominated non-point source pollution, such as agricultural and urban runoff, whereas mixed source pollution dominated in the MP and HP zones. These results provide information to be used for developing better pollution control strategies for the river network of Serbia.

Ammonia emissions at the national level are frequently estimated by applying the emission inventory approach, which includes the use of emission factors, which are difficult and expensive to determine. Emission factors are therefore the subject of estimation, and as such they contribute to inherent uncertainties in the estimation of ammonia emissions. This paper presents an alternative approach for the prediction of ammonia emissions at the national level based on artificial neural networks and broadly available sustainability and economical/agricultural indicators as model inputs. The Multilayer Perceptron (MLP) architecture was optimized using a trial-and-error procedure, including the number of hidden neurons, activation function, and a back-propagation algorithm. Principal component analysis (PCA) was applied to reduce mutual correlation between the inputs. The obtained results demonstrate that the MLP model created using the PCA transformed inputs (PCA-MLP) provides a more accurate prediction than the MLP model based on the original inputs. In the validation stage, the MLP and PCA-MLP models were tested for ammonia emission predictions for up to 2 years and compared with a principal component regression model. Among the three models, the PCA-MLP demonstrated the best performance, providing predictions for the USA and the majority of EU countries with a relative error of less than 20 %.

Biological oxygen demand (BOD) is the most significant water quality parameter and indicates water pollution with respect to the present biodegradable organic matter content. European countries are therefore obliged to report annual BOD values to Eurostat; however, BOD data at the national level is only available for 28 of 35 listed European countries for the period prior to 2008, among which 46 % of data is missing. This paper describes the development of an artificial neural network model for the forecasting of annual BOD values at the national level, using widely available sustainability and economical/industrial parameters as inputs. The initial general regression neural network (GRNN) model was trained, validated and tested utilizing 20 inputs. The number of inputs was reduced to 15 using the Monte Carlo simulation technique as the input selection method. The best results were achieved with the GRNN model utilizing 25 % less inputs than the initial model and a comparison with a multiple linear regression model trained and tested using the same input variables using multiple statistical performance indicators confirmed the advantage of the GRNN model. Sensitivity analysis has shown that inputs with the greatest effect on the GRNN model were (in descending order) precipitation, rural population with access to improved water sources, treatment capacity of wastewater treatment plants (urban) and treatment of municipal waste, with the last two having an equal effect. Finally, it was concluded that the developed GRNN model can be useful as a tool to support the decision-making process on sustainable development at a regional, national and international level.

Ammonia emissions at the national level are frequently estimated by applying the emission inventory approach, which includes the use of emission factors, which are difficult and expensive to determine. Emission factors are therefore the subject of estimation, and as such they contribute to inherent uncertainties in the estimation of ammonia emissions. This paper presents an alternative approach for the prediction of ammonia emissions at the national level based on artificial neural networks and broadly available sustainability and economical/agricultural indicators as model inputs. The Multilayer Perceptron (MLP) architecture was optimized using a trial-and-error procedure, including the number of hidden neurons, activation function, and a back-propagation algorithm. Principal component analysis (PCA) was applied to reduce mutual correlation between the inputs. The obtained results demonstrate that the MLP model created using the PCA transformed inputs (PCA-MLP) provides a more accurate prediction than the MLP model based on the original inputs. In the validation stage, the MLP and PCA-MLP models were tested for ammonia emission predictions for up to 2 years and compared with a principal component regression model. Among the three models, the PCA-MLP demonstrated the best performance, providing predictions for the USA and the majority of EU countries with a relative error of less than 20 %.

Biological oxygen demand (BOD) is the most significant water quality parameter and indicates water pollution with respect to the present biodegradable organic matter content. European countries are therefore obliged to report annual BOD values to Eurostat; however, BOD data at the national level is only available for 28 of 35 listed European countries for the period prior to 2008, among which 46 % of data is missing. This paper describes the development of an artificial neural network model for the forecasting of annual BOD values at the national level, using widely available sustainability and economical/industrial parameters as inputs. The initial general regression neural network (GRNN) model was trained, validated and tested utilizing 20 inputs. The number of inputs was reduced to 15 using the Monte Carlo simulation technique as the input selection method. The best results were achieved with the GRNN model utilizing 25 % less inputs than the initial model and a comparison with a multiple linear regression model trained and tested using the same input variables using multiple statistical performance indicators confirmed the advantage of the GRNN model. Sensitivity analysis has shown that inputs with the greatest effect on the GRNN model were (in descending order) precipitation, rural population with access to improved water sources, treatment capacity of wastewater treatment plants (urban) and treatment of municipal waste, with the last two having an equal effect. Finally, it was concluded that the developed GRNN model can be useful as a tool to support the decision-making process on sustainable development at a regional, national and international level.

In this paper, we have analyzed parts of printed circuit board (PCB) and liquid crystal display (LCD) screens of mobile phones and computers, quantitative and qualitative chemical compositions of individual components, and complete PCBs were determined. Differential thermal analysis (DTA) and differential scanning calorimetry (DSC) methods were used to determine the temperatures of phase transformations, whereas qualitative and quantitative compositions of the samples were determined by X-ray fluorescence spectrometry (XRF), inductively coupled plasma optical emission spectrometry (ICP-OES), and scanning electron microscopy (SEM)-energy dispersive X-ray spectrometry (EDS) analyses. The microstructure of samples was studied by optical microscopy. Based on results of the analysis, a procedure for recycling PCBs is proposed. The emphasis was on the effects that can be achieved in the recycling process by extraction of some parts before the melting process. In addition, newly developed materials can be an adequate substitute for some of the dangerous and harmful materials, such as lead and arsenic are proposed, which is in accordance with the European Union (EU) Restriction of the use of certain hazardous substances (RoHS) directive as well as some alternative materials for use in the electronics industry instead of gold and gold alloys.

In this paper, we have analyzed parts of printed circuit board (PCB) and liquid crystal display (LCD) screens of mobile phones and computers, quantitative and qualitative chemical compositions of individual components, and complete PCBs were determined. Differential thermal analysis (DTA) and differential scanning calorimetry (DSC) methods were used to determine the temperatures of phase transformations, whereas qualitative and quantitative compositions of the samples were determined by X-ray fluorescence spectrometry (XRF), inductively coupled plasma optical emission spectrometry (ICP-OES), and scanning electron microscopy (SEM)-energy dispersive X-ray spectrometry (EDS) analyses. The microstructure of samples was studied by optical microscopy. Based on results of the analysis, a procedure for recycling PCBs is proposed. The emphasis was on the effects that can be achieved in the recycling process by extraction of some parts before the melting process. In addition, newly developed materials can be an adequate substitute for some of the dangerous and harmful materials, such as lead and arsenic are proposed, which is in accordance with the European Union (EU) Restriction of the use of certain hazardous substances (RoHS) directive as well as some alternative materials for use in the electronics industry instead of gold and gold alloys.

In this paper, we have analyzed parts of printed circuit board (PCB) and liquid crystal display (LCD) screens of mobile phones and computers, quantitative and qualitative chemical compositions of individual components, and complete PCBs were determined. Differential thermal analysis (DTA) and differential scanning calorimetry (DSC) methods were used to determine the temperatures of phase transformations, whereas qualitative and quantitative compositions of the samples were determined by X-ray fluorescence spectrometry (XRF), inductively coupled plasma optical emission spectrometry (ICP-OES), and scanning electron microscopy (SEM)-energy dispersive X-ray spectrometry (EDS) analyses. The microstructure of samples was studied by optical microscopy. Based on results of the analysis, a procedure for recycling PCBs is proposed. The emphasis was on the effects that can be achieved in the recycling process by extraction of some parts before the melting process. In addition, newly developed materials can be an adequate substitute for some of the dangerous and harmful materials, such as lead and arsenic are proposed, which is in accordance with the European Union (EU) Restriction of the use of certain hazardous substances (RoHS) directive as well as some alternative materials for use in the electronics industry instead of gold and gold alloys.