Metal leachability, heavy metals, polycyclic aromatic hydrocarbons and polychlorinated biphenyls in fly and bottom ashes of a medical waste incineration facility

Medical waste from hospitals and other healthcare institutions has become an imperative environmental and public safety problem. Medical waste in Greece has become one of the most urgent environmental problems, because there are 14,000 tons produced annually, of which only a small proportion is incinerated. In the prefecture of Attica there is only one modern municipal medical waste incinerator (started 2004) burning selected infectious hospital waste (5-6 tons day(-1)). Fly and bottom residues (ashes) are collected and stored temporarily in barrels. High values of metal leachability prohibit the landfilling of these ashes, as imposed by EU directives. In the present study we determined quantitatively the heavy metals and other elements in the fly and bottom ashes of the medical waste incinerator, by inductively coupled plasma emission spectrometry (ICP) and by energy dispersive X-ray analysis (EDAX). Heavy metals, which are very toxic, such as Pb, Cd, Ni, Cr, Cu and Zn were found in high concentrations in both fly and bottom ashes. Metal leachability of fly and bottom ashes by water and kerosene was measured by ICP and the results showed that toxic metals in both ashes, such as Pb, Cr, Cd, Cu and Zn, have high leaching values. These values indicate that metals can become soluble and mobile if ash is deposited in landfills, thus restricting their burial according to EU regulations. Analysis of polychlorinated biphenyls and polycyclic aromatic hydrocarbons in fly and bottom ashes showed that their concentrations were very low. This is the first known study in Greece and the results showed that incineration of medical waste can be very effective in minimizing the most hazardous and infectious health-care waste. The presence of toxic metals with high leachability values remains an important draw back of incineration of medical waste and various methods of treating these residues to diminish leaching are been considered at present to overcome this serious technical problem.     

Immobilized-cell-augmented activated sludge process for treating wastewater containing hazardous compounds.

A novel bioaugmentation scheme called immobilized-cell-augmented activated sludge (ICAAS) was developed. Offline enricher reactors were used to maintain immobilized acclimated cells applied to augment completely mixed activated sludge (CMAS) treating a pentachlorophenol (PCP) pulse loading. Cellulose triacetate (CA) and powder activated carbon (PAC) combined with CA (PAC + CA) were the two media types used for entrapping the PCP-degrading culture. With ICAAS at 5% by volume augmentation, PCP removal of 73.1 and 75.1% via biodegradation, volatilization, and adsorption onto suspended cells, entrapped cells, and media was achieved for the systems with CA and PAC + CA media, respectively, while PCP removal in a control CMAS, which had a comparable level of combined PCP adsorption onto suspended cells and volatilization as the ICAAS, was 48.7%. Results further showed that the immobilized cells retained their PCP-degrading ability when they were fed with the inducer (PCP) once every 20 days.     

Metals removal from aqueous solution by iron-based bonding agents

GOAL AND SCOPE AND BACKGROUND: The application of a promising method, termed sorptive flotation, for the removal of chromium(VI) and zinc ions was the aim of the present paper. A special case of sorptive flotation is adsorbing colloid flotation. Suitable sorbent preparation techniques have been developed in the laboratory. METHODS: Sorptive flotation, consisting of the sorption and flotation processes combined in series, has proved to give fast and satisfactory treatment of the industrial streams and effluents bearing dilute aqueous solutions of zinc and chromium(VI). RESULTS AND DISCUSSION: Goethite has proved to be effective for the removal of chromium(VI) and zinc ions. Also, adsorbing colloid flotation with ferric hydroxide (as the co-precipitant) could be an alternative method to the above-mentioned separation of metal ions. In both cases, chromium(VI) (pH=4) and zinc (pH=7) removal was about 100%. CONCLUSION: The reasons for selecting the iron-based bonding materials, like goethite and/or in-situ produced ferric hydroxide, are that they are cheap, easily synthesized, suitable both for cation and anion sorption, and, furthermore, that they present low risks for adding a further pollutant to the system. Promising results were obtained. RECOMMENDATION AND OUTLOOK: The application of goethite and in-situ produced ferric hydroxide has demonstrated their effectiveness in the removal of heavy metal ions, such as chromium anions and zinc cations. A proposed continuation of current work is the utilization of similar iron oxides, for instance synthesized akaganeite. The comparison between the results reported in this paper with the results reported in the literature, also deserves attention.     

Combining neural network models to predict spatial patterns of airborne pollutant accumulation in soils around an industrial point emission source

Neural networks (NNs) have the ability to model a wide range of complex nonlinearities. A major disadvantage of NNs, however, is their instability, especially under conditions of sparse, noisy, and limited data sets. In this paper, different combining network methods are used to benefit from the existence of local minima and from the instabilities of NNs. A nonlinear k-fold cross-validation method is used to test the performance of the various networks and also to develop and select a set of networks that exhibits a low correlation of errors. The various NN models are applied to estimate the spatial patterns of atmospherically transported and deposited lead (Pb) in soils around an historical industrial air emission point source. It is shown that the resulting ensemble networks consistently give superior predictions compared with the individual networks because, for the ensemble networks, R2 values were found to be higher than 0.9 while, for the contributing individual networks, values for R2 ranged between 0.35 and 0.85. It is concluded that combining networks can be adopted as an important component in the application of artificial NN techniques in applied air quality studies.     

Are savannas patch-dynamic systems? A landscape model

Savannas are ecosystems characterized by the coexistence of woody species (trees and bushes) and grasses. Given that savanna characteristics are mainly formed from competition, herbivory, fire, woodcutting, and patchy soil and precipitation characteristics, we propose a spatially explicit model to examine the effects of the above-mentioned parameters on savanna vegetation dynamics in space and time. Furthermore, we investigate the effects of the above-mentioned parameters on tree–bush–grass ratios, as well as the degrees of aggregation of tree–bush–grass biomass. We parameterized our model for an arid savanna with shallow soil depth as well as a mesic one with generally deeper and more variable soil depths. Our model was able to reproduce savanna vegetation characteristics for periods of time over 2000 years with daily updated time steps. According to our results, tree biomass was higher than bush biomass in the arid savanna but bush biomass exceeded tree and grass biomass in the simulated mesic savanna. Woody biomass increased in our simulations when the soil's porosity values were increased (mesic savanna), in combination with higher precipitation. Savanna vegetation varied from open savanna to woodland and back to open savanna again. Vegetation cycles varied over ∼300-year cycles in the arid and ∼220-year cycles in the mesic-simulated savanna. Autocorrelation values indicated that there are both temporal and spatial vegetation cycles. Our model indicated cycling savanna vegetation at the landscape scale, cycles in cells, and patchiness, i.e. patch dynamics.     

Metabolic and molecular stress responses of the gilthead seabream Sparus aurata during long-term exposure to increasing temperatures

Tolerance to a changing climate regime and persistence in the natural environment depends on the limited capacity to acclimate to changing temperatures. The present study aimed to identify and characterize thermal limits of the Mediterranean fish Sparus aurata as well as the processes providing heat protection during exposure to high temperatures. Processes studied included heat shock protein expression, protein kinase activity and metabolic adjustments. Molecular responses were addressed through the expression of Hsp70 and Hsp90 and the phosphorylation of stress-activated protein kinases, p38 mitogen-activated protein kinase (p38 MAPK) and cJun-N-terminal kinases (JNKs). Thermal impacts on metabolic capacities were assessed by studying the maximum activities of citrate synthase (CS), malate dehydrogenase (MDH) and 3-hydroxyacyl CoA dehydrogenase (HOAD) as well as pyruvate kinase (PK) and lactate dehydrogenase (L-LDH). The expression of Hsp70 and hsp90 was activated when the fish were exposed to temperatures beyond 20°C. Increased phosphorylation of p38 MAPK and JNKs indicated the parallel activation of MAPK signaling cascades and the potential involvement of MAPKs in the induction of Hsp genes. Exposure to extreme temperatures beyond 24°C caused an increase in the enzymatic activity of PK and LDH indicating an enhanced glycolytic potential.     

In situ sensing of subsurface contamination—part I: near-infrared spectral characterization of alkanes,aromatics, and chlorinated hydrocarbons

There is an imperative need for a chemical sensor capable of remote, in situ, long-term monitoring of chemical species at sites containing toxic chemical spills, specifically at chemical waste dumps, landfills, and locations with underground storage tanks. In the current research, a series of experiments were conducted measuring the near-infrared optical absorption of alkanes, aromatics, and chlorinated hydrocarbons. A spectral library was then developed to characterize the optical spectra of liquid hydrocarbons. Near-infrared analysis was chosen due to compatibility with optical fibers. The goal was to differentiate between classes of hydrocarbons and to also discriminate between compounds within a class of similar molecular structures. It was observed that unique absorption spectra can be obtained for each hydrocarbon, and this uniqueness can be used to discriminate between hydrocarbons from different families. Statistical analyses, namely, principal component analysis (PCA) and correlation coefficient (Spearman and Pearson methods), were attempted to match absorption spectra from an unknown hydrocarbon with the database with limited success. An algorithm was subsequently written to identify the characteristic peaks of each hydrocarbon that could be used to match data from an unknown chemical species with the database.     

Part I: Temporal and spatial distribution of multiclass pesticide residues in lake waters of Northern Greece: application of an optimized SPE-UPLC-MS/MS pretreatment and analytical method

The present work describes the application of an analytical procedure, utilizing ultra performance liquid chromatography (UPLC) coupled with mass spectrometry instrumentation, for the determination of 253 multiclass pesticides, classified in six different groups. Solid phase extraction was applied for the isolation and pre-concentration of target compounds in water samples. Surface waters of the lakes located in Northern Greece (Volvi, Doirani, and Kerkini), were collected in two time periods (fall/winter 2010 and spring/summer 2011) and analyzed, applying the developed analytical methods. Spatial distribution of detected pesticides was visualized using interpolation methods and geographical information systems (GIS). Pesticides with maximum concentrations were amitrole, propoxur, simazine, chlorpyrifos, carbendazim, triazophos, disulfoton-sulfone, pyridaben, sebuthylazine, terbuthylazine, atrazine, atrazine-desethyl, bensulfuron-methyl, metobromuron, metribuzin, rotenone, pyriproxyfen, and rimsulfuron. In Lake Kerkini, mainly carbamates and triazines were determined at elevated concentrations, near the coastal point of the NW side of the lake. Seasonal variations were strong among the applied pesticide classes and determined concentrations, indicating the contribution of pesticide application patterns and rainfall. Lake Doirani exhibited organophosphate pesticides at higher concentrations mainly at coastal points, while triazines emerged as the main pollutant during spring sampling. Lake Volvi exhibited the highest pesticide concentrations, mostly triazines and ureas at the central part of the lake. The occurrence of extreme values and nonconstant seasonal variations indicated that the concentrations were increased disproportionately during the second sampling, as a result of the varying contribution of pollution sources right after the application period. In all cases, the total concentration of pesticides increased during the second sampling period.     

Effectiveness of urea in enhancing the extractability of 2,4,6-trinitrotoluene from chemically variant soils

One of the major challenges in developing an effective phytoremediation technology for 2,4,6-trinitrotoluene (TNT) contaminated soils is limited plant uptake resulting from low solubility of TNT. The effectiveness of urea as a solubilizing agent in increasing plant uptake of TNT in hydroponic systems has been documented. Our preliminary greenhouse experiments using urea were also very promising, but further characterization of the performance of urea in highly-complex soil-solution was necessary. The present study investigated the natural retention capacity of four chemically variant soils and optimized the factors influencing the effectiveness of urea in enhancing TNT solubility in the soil solutions. Results show that the extent of TNT sorption and desorption varies with the soil properties, and is mainly dependent on soil organic matter (SOM) content. Hysteretic desorption of TNT in all tested soils suggests irreversible sorption of TNT and indicates the need of using an extractant to increase the release of TNT in soil solutions. Urea significantly (p < 0.0001) enhanced TNT extraction from all soils, by increasing its solubility at the solid/liquid interface. Soil organic matter content and urea application rates showed significant effects, whereas pH did not exert any significant effect on urea catalysis of TNT extraction from soil. The optimum urea application rates (125 or 350 mg kg⁻¹) for maximizing TNT extraction were within the limits set by the agronomic fertilizer-N rates used for major agricultural crops. The data obtained from this batch study will facilitate the optimization of a chemically-catalyzed phytoremediation model for cleaning up TNT-contaminated soils.