In the present work, the effectiveness of conventional wastewater treatments (activated sludge and oxidation ditches) and low-cost wastewater treatments (trickling filter beds, anaerobic lagooning and constructed wetlands) in the removal of pharmaceutically active compounds has been studied. To evaluate the efficiency of removal, 16 pharmaceutically active compounds belonging to seven therapeutic groups (anti-inflammatory drugs, antibiotics, antiepileptic drugs, β-blockers, nervous stimulants, estrogens and lipid regulators) have been monitored during 1-year period in influent and effluent wastewater from 11 wastewater treatment plants of Spain. Mean removal rates of pharmaceutically active compounds achieved in conventional wastewater treatments were slightly higher than those achieved in low-cost treatments, being 64% and 55%, respectively. Ibuprofen, naproxen, salicylic acid and caffeine were the pharmaceutical compounds most efficiently removed, regardless the wastewater treatment applied, with removal rates up to 99%. Anaerobic lagooning was the less effective treatment for the removal of the most persistent compounds: carbamazepine and propranolol.

We present in this paper a new strategy based on the use of polynomial chaos expansion (PCE) for both global sensitivity analysis and parameter optimization. To limit the number of evaluations of the direct model, we develop a simple and efficient procedure to construct a sparse PCE where only coefficients that have a significant contribution to the variance of the model are retained. Parameter estimation is performed using an adaptive procedure where the intervals of variation of the parameters are progressively reduced using information from sensitivity analysis calculated using the sparse PCE. The strategy is shown to be effective for the parameter estimation of two reactive transport problems: a synthetic reactive transport problem involving the Freundlich sorption isotherm and a field experiment of Valocchi et al. (Water Resources Research 17:1517–1527, 1981) involving nonlinear ion exchange reactions.

Gas dispersion in a set of three different porous materials with similar particle size, as a function of material tortuosity and anisotropy ratio, was investigated. The materials were packed with different spatial orientations of the individual particles so as to create media with different tortuosity and anisotropy ratios. Three different media (slate chips, wood chips, and pebbles) and four particle orientations have been used to generate a total of nine different porous media mimicking single porosity, dual porosity isotropic, anisotropic, aggregated, or granular materials. Resulting values of tortuosity and anisotropy ratio for each medium were determined via measurements of gas permeability and molecular gas diffusion coefficient. These values were then compared to measured values of gas dispersivity for each medium. The results showed that dispersivity is inversely proportional to tortuosity but directly proportional to anisotropy ratio and that the relations were approximately linear within the range of tortuosities and anisotropy ratios investigated. Wood chips (dual porosity material) yielded higher values of gas dispersivity compared to slate chips (single porosity material). A likely reason is in part the difference in pore structure between the materials and in part a difference in particle surface roughness (which was highest for wood chips) both of which affects dispersion.

This study presents the application of multivariate statistical tools for the evaluation of spatial variations and the interpretation of water quality data obtained in a monitoring program of Lis river basin surface water, Portugal. Twenty-seven physicochemical and microbiological parameters were determined in six water sampling campaigns at 16 monitoring sites during the period from September 2003 to November 2006. Correlation analysis, principal component analysis, and cluster analysis were performed to evaluate the main water pollution sources and to characterize the spatial distribution of water pollution profiles in river basin. The results achieved with the statistical methodologies led to distinguish natural and anthropogenic pollution sources. Additionally, monitoring sites with similar water pollution profile were identified, indicating that some monitoring locations can be changed to improve the spatial characterization of water quality in the river basin. CBO, CQO, P, and N were identified as significant variables affecting spatial variations, namely in the Lis river middle reach. Besides the identification of main pollution sources, the applied statistical tools were able to identify spatial patterns of water pollution in Lis river basin, which further helps in the reassessment of the number and location of monitoring sites.

The goal of our study was to identify pharmaceuticals, their potential sources and consumption level in two different socioeconomic and geographical regions—Bordeaux, France and Kharkiv, Ukraine. These substances were monitored in rivers water during contrasted seasonal conditions with application of passive samplers. The 21 pharmaceuticals (psychiatric drugs: alprazolam, amitriptyline, diazepam, fluoxetine, nordiazepam, carbamazepine, bromazepam; analgesics: aspirin, paracetamol; broncholidator: clenbuterol, salbutamol, terbutaline; non-steroidal anti-inflammatory drug: diclofenac, ibuprofen, ketoprofen, naproxen; lipid regulator: gemfibrozil; stimulants: caffeine, theophylline) were identified in sites upstream and downstream of urban areas and discharge of wastewaters. Caffeine, carbamazepine, and diclofenac were relatively abundant into the surface water and could be considered as potential anthropogenic markers of wastewater discharges into rivers. A mass balance modeling has been applied to calculate approximate consumption rates for carbamazepine, diclofenac, and caffeine in both regions to assess socio-economic factors linked with pharmaceuticals behavior.

Following the Deepwater Horizon explosion and crude oil contamination of a marsh ecosystem in AL in June 2010, hydrocarbon-degrader microbial abundances of aerobic alkane, total hydrocarbon, and polycyclic aromatic hydrocarbon (PAH) degraders were enumerated seasonally. Surface sediment samples were collected in October and December of 2010 and in April and July of 2011 along 40–70-m transects from the high tide to the intertidal zone including Spartina alterniflora-vegetated marsh, seagrass (Ruppia maritima)-dominated sediments, and nonvegetated sediments. Alkane and total hydrocarbon degraders in the sediment were detected, while PAH degraders were below detection limit at all locations examined during the sampling periods. The highest counts for microbial alkane degraders were observed at the high tide line in April and averaged to 8.65 × 105 of cells/g dry weight (dw) sediment. The abundance of alkane degraders during other months ranged from 9.49 × 103 to 3.87 × 104, while for total hydrocarbon degraders, it ranged between 5.62 × 103 and 1.14 × 105 of cells/g dw sediment. Pore water nutrient concentrations (NH 4 + , NO 3 − , NO 2 − , and PO 4 3− ) showed seasonal changes with minimum values observed in December and April and maximum values in October and July. Concentrations of total petroleum hydrocarbons in sediments averaged 100.4 ± 52.4 and 141.9 ± 57.5 mg/kg in January and July, 2011, respectively. The presence of aerobic microbial communities during all seasons in these nearshore ecosystems suggests that an active and resident microbial community is capable of mineralizing a fraction of petroleum hydrocarbons.

The magnetic, nanocrystalline Fe₀.₂(Co₂₀Ni₈₀)₀.₈ alloy porous microfibers were prepared by the citrate gel thermal decomposition and reduction process. The morphology, chemical composition, microstructure, and magnetic properties of the microfibers were investigated by X-ray diffraction, field emission scanning electron microscopy, energy-dispersive X-ray, Brunauere–Emmette–Teller, and vibration sample magnetometer. The as-prepared magnetic, nanocrystalline Fe₀.₂(Co₂₀Ni₈₀)₀.₈ porous microfibers consisting of about 48 nm grains are characterized by diameters of 1–4 μm, specific surface area of 17.73 m²/g, and specific magnetization of 196.7 Am²/kg. The arsenic(V) absorption on these magnetic Fe₀.₂(Co₂₀Ni₈₀)₀.₈ porous microfibers at room temperature was determined by the ICP-AES measurement of arsenic(V) in aqueous solution. The results show that the pseudo-first-order kinetic model is consistent with the arsenic(V) adsorption process and a good correlation coefficient (R ² = 0.9862). By comparing among the Langmuir, Freundlich, Temkin, and Redlich–Peterson models for adsorption isotherms of arsenic(V) onto the magnetic Fe₀.₂(Co₂₀Ni₈₀)₀.₈ porous microfibers at room temperature, the Freundlich model and Redlich–Peterson model can be used to evaluate the arsenic(V) adsorption isotherm at room temperature. The arsenic(V) equilibrium absorbance of the magnetic Fe₀.₂(Co₂₀Ni₈₀)₀.₈ porous microfibers is up to 1.9 mg/g when the initial arsenic(V) concentration is 1.0 mg/L in aqueous solution.

Bioremediation strategies, including biostimulation, exogenous bioaugmentation and autochthonous bioaugmentation, were evaluated to determine their ability to degrade petroleum hydrocarbons in two recently polluted agricultural soils, one with a clayey texture and a silty loam soil. It was hypothesized in this work that the bioavailability of the pollutant may depend on the soil type, which would determine the biodegradation rate and the correct methodology to be used. The soils were artificially contaminated with diesel fuel, and several soil–water suspension batch microcosm experiments were conducted to observe the bioremediation process. The inocula used in the experiments included an autochthonous soil consortium and an exogenous consortium that had been acclimated to diesel consumption. The clayey soil desorbed diesel quickly, while the silty soil, with a higher organic content, did not. Hydrocarbon availability was limited in the latter case. After 48 h of treatment, the diesel removal efficiency in the clayey soil was clearly higher than that in the silty soil. However, after 11 days, the efficiencies were similar, and more than 95% of the diesel was biodegraded in most experiments. According to the efficiency and bioavailability analyses, the best methodology to bioremediate the silty soil was biostimulation with the native consortium. In contrast, bioaugmentation with a combination of native and exogenous consortia was chosen to treat the clayey soil. The results of this study suggest that when pollutants are easily available, bioaugmentation can successfully remediate the pollution. However, when availability is limited, biostimulation can be more efficient.

We present the concept of assemblage tolerance profiles (ATPs) as an aid to freshwater bioassessment, and illustrate it with a practical example. An ATP describes the proportion of taxa in an observed assemblage that is estimated to tolerate each level of a specific stressor within a defined range. We used an extensive compilation of biomonitoring field data to estimate the lower tolerances for pH and dissolved oxygen (DO) of common families of macroinvertebrates in rivers of south-eastern Australia. These limits were then used to establish ATPs for macroinvertebrate assemblages at 30 sites across six river systems with varying levels of exposure to drainage from disused mines and discharges from sewage treatment plants. We hypothesised that sites with more exposure to mine drainage would have ATPs indicating greater tolerance of low pH, whereas sites with more exposure to sewage discharges would have ATPs indicating greater tolerance of low DO, and found that these hypotheses were confirmed for five of the six river systems. We suggest that stressor-specific ATPs, based on tolerances derived from either field distributions or laboratory tests, can help to verify or eliminate candidate causes of inferred human impacts on aquatic ecosystems.

The aim of this study was to investigate the removal of both polycyclic aromatic hydrocarbons (PAHs) and heavy metals from field-contaminated sediments by activated persulfate oxidation. Various chemicals, including hydroxypropyl-β-cyclodextrin (HPCD), S,S-ethylenediaminedisuccinic acid (EDDS), tetrasodium pyrophosphate (Na₄P₂O₇), and hydrochloric acid (HCl), were applied individually before or after activated persulfate oxidation to enhance the co-removal of both types of pollutants. It was found that the organic removal efficiency was not significantly enhanced by increasing the concentration of HPCD from 2.5 to 5.0 mM. The removal efficiency of heavy metals was not improved even at an excess amount of EDDS after activated persulfate oxidation. However, the addition of EDDS acted as the Fe²+ carrier for activated persulfate oxidation. In addition, no significant enhancement of heavy metal removal was observed by increasing the concentrations of Na₄P₂O₇ and HCl from 0.01 to 0.1 M after activated persulfate oxidation. However, comparing 0.1 M HCl with 0.1 M Na₄P₂O₇, HCl was shown to be more effective in promoting the removal of organic pollutants. With further adjustments on the experimental conditions, the highest removal amount of metals and PAHs was achieved by adding 2 M of HCl with 3 days mixing, followed by Fe²+-activated persulfate oxidation (PS/Fe²+ molar ratio at 4:1) for further 6 h mixing. The removal efficiency of low and high molecular weight PAHs was about 70 and 20 %, respectively, while the removal efficiency of metals was 70, 100, 40, 65, 65, 80, and 100 % for Cr, Cu, Hg, Mn, Ni, Pb, and Zn, respectively.