Photocatalytic degradation of dissolved organic carbon (DOC) by utilizing Fe(III)-doped TiO2 at the visible radiation range is hereby reported. The photocatalyst was immobilized on sintered glass frits with the coating done by wet method, calcinated at 500 °C and then applied in a photodegradation reactor. The addition of a transition metal dopant, Fe(III), initiated the red shift which was confirmed by UV-Vis spectroscopy, and the photocatalyst was activated by visible radiation. X-ray diffraction patterns showed that Fe(III) doping had an effect on the crystallinity of the photocatalysts. Mixtures of DOC and associated coloured solutions were degraded in first-order kinetics, showing that the degradation process was not dependent on intermediates or other species in solution. A reactor with a catalyst coating area of 12.57 cm(2) was able to degrade 0.623 mg of the dissolved material per minute. Exposure of the reactor to hostile acidic conditions and repeated use did not compromise its efficiency. It was observed that the reactor regenerates itself in the presence of visible light, and therefore, it can be re-used for more than 100 runs before the performance dropped to <95 %. The results obtained indicate that the photocatalyst reactor has a great potential of application for use in tandem with biosorbent cartridges to complement water purification methods for domestic consumption.

The potential of the microbial communities present in the intertidal zone of an unimpacted beach (a beach that did not suffer any significant oil spill) to degrade hydrocarbons was investigated. For that, laboratory-based microcosms (50-ml flasks) were set up with sandy beach sediment spiked with crude oil and incubated with local seawater for 15 days in the dark. Three bioremediation treatments were tested (biostimulation (BS), autochthonous bioaugmentation (AB), and combined treatment of biostimulation + bioaugmentation (BS + AB)) and the results were compared with natural attenuation (NA). Visual inspection showed clearly an oil solubility increase (confirmed by a higher hydrocarbons concentration in supernatant solutions) for all tested treatments when compared to NA. Significant degradation of the oil, shown by different profiles of petroleum hydrocarbons, was also observed for the different treatments particularly for BS + AB. Therefore, the microbial community of this unimpacted beach sediment could respond to an oil spill, degrading hydrocarbons. But to increase the natural attenuation pace, obtained results indicated that BS + AB is an appropriate approach for the bioremediation of beaches recently impacted by an oil spill. The autochthonous microbial cultures can be obtained “before” or “after” the contamination of the target site, being inoculated into the site right after it contamination.

Wastewater treatment is an important source of nitrous oxide (N₂O), which is a strong greenhouse gas and dominate ozone-depleting substance. The purpose of this study was to evaluate the effect of carbon source on N₂O emission from anoxic/oxic biological nitrogen removal process. The mechanisms of N₂O emission were also studied. Long-term experiments were operated to evaluate the effect of three different carbon sources (i.e., glucose, sodium acetate, and soluble starch) on N₂O emission characteristics. And batch experiments, in the presence or absence of specific inhibitors, were carried out to identify the sources of N₂O emission. The ammonia-oxidizing bacteria (AOB) and denitrifiers community compositions under different circumstances were also analyzed based on which the underlying mechanisms of N₂O emission were elucidated. The conversion ratios of N₂O in reactors with glucose, sodium acetate, and soluble starch were 5.3 %, 8.8 %, and 2.8 %, respectively. The primary process responsible for N₂O emission was nitrifier denitrification by Nitrosomonas-like AOB, while denitrification by heterotrophic denitrifiers acted as the sink. Reactor with sodium acetate showed the highest N₂O emission, together with the highest nitrogen and phosphate removal ratios. Carbon source has a significant impact on N₂O emission quantity and relatively minor effect on its production mechanism.

Although the long incubation time of biochemical oxygen demand (BOD₇) measurements has been addressed by the use of microbial biosensors, the resulting sensor-BOD values gained from the measurements with specific industrial wastewaters still underestimates the BOD value of such samples. This research aims to provide fast and more accurate BOD measurements in the dairy wastewater samples. Unlike municipal wastewater, wastewater from the dairy industry contains many substrates that are not easily accessible to a majority of microorganisms. Therefore, a bacterial culture, Microbacterium phyllosphaerae, isolated from dairy wastewater was used to construct a semi-specific microbial biosensor. A universal microbial biosensor based on Pseudomonas fluorescens, which has a wide substrate spectrum but is nonspecific to dairy wastewater, was used as a comparison. BOD biosensors were calibrated with OECD synthetic wastewater, and experiments with different synthetic and actual wastewater samples were carried out. Results show that the semi-specific M. phyllosphaerae-based microbial biosensor is more sensitive towards wastewaters that contain milk derivates and butter whey than the P. fluorescens-based biosensor. Although the M. phyllosphaerae biosensor underestimates the BOD₇ value of actual dairy wastewaters by 25–32 %, this bacterial culture is more suitable for BOD monitoring in dairy wastewater than P. fluorescens, which underestimated the same samples by 46–61 %.

Since data on mercury (Hg) levels in Caucasians and African Americans (AAs) of both genders are lacking, this study aims to present toenail Hg distributions and explore the potential determinants using data from the Coronary Artery Risk Development in Young Adults Trace Element Study. Data from 4,344 Americans, aged 20–32 in 1987, recruited from Oakland, Chicago, Minneapolis, and Birmingham were used to measure toenail Hg levels by instrumental neutron-activation method. The Hg distribution was described with selected percentiles and geometric means. Multivariable linear regression (MLR) was used to examine potential determinants of Hg levels within ethnicity–gender subgroups. The geometric mean of toenail Hg was 0.212 (95 % CI = 0.207–0.218) μg/g. Hg levels varied geographically with Oakland the highest [0.381 (0.367–0.395) μg/g] and Minneapolis the lowest [0.140 (0.134–0.147) μg/g]. MLR analyses showed that male gender and AA ethnicity were negatively associated with toenail Hg levels, and that age, living in Oakland city, education level, alcohol consumption, and total fish intake were positively associated with toenail Hg concentrations within each ethnicity–gender subgroup. Current smokers were found to have higher Hg only in AA men. This study suggested age, gender, ethnicity, study center, alcohol, education level, and fish consumption consistently predict toenail Hg levels. As fish consumption was the key determinant, avoiding certain types of fish that have relatively high Hg levels may be crucial in reducing Hg intake.

Soybean stover-derived biochar was used to immobilize lead (Pb) in military firing range soil at a mass application rate of 0 to 20 wt.% and a curing period of 7 days. The toxicity characteristic leaching procedure (TCLP) was performed to evaluate the effectiveness of the treatment. The mechanism responsible for Pb immobilization in military firing range soil was evaluated by scanning electron microscopy-energy dispersive x-ray spectroscopy (SEM-EDX) and x-ray absorption fine structure (XAFS) spectroscopy analyses. The treatment results showed that TCLP Pb leachability decreased with increasing biochar content. A reduction of over 90 % in Pb leachability was achieved upon treatment with 20 wt.% soybean stover-derived biochar. SEM-EDX, elemental dot mapping and XAFS results in conjunction with TCLP leachability revealed that effective Pb immobilization was probably associated with the pozzolanic reaction products, chloropyromorphite and Pb-phosphate. The results of this study demonstrated that soybean stover-derived biochar was effective in immobilizing Pb in contaminated firing range soil.

Sulfonylurea herbicides are extensively widespread for the protection of a variety of crops and vegetables because of their low application rates, high selectivity and low persistency in the environment; unfortunately, their low persistence does not always correspond to a lower toxicity, since new species potentially more toxic and stable than the precursor herbicides can form, owing to natural degradation processes. Here, the photodegradation of amidosulfuron in aqueous solutions was studied by high-performance liquid chromatography with diode array detection and tandem mass spectrometry to identify the degradation products in order to outline the environmental fate of the molecules generating from the simulation of one of the natural processes that can occur, i.e., photoinduced degradation. The photodegradation process results in a first order kinetic reaction with a t₁/₂value of 276 h (11.5 days) and a kinetic constant of 0.0027 h⁻¹, and three possible degradation products were identified. The results obtained are then compared to those obtained in previous works carried out in comparable experimental conditions about nicosulfuron and tribenuron-methyl, two sulfonylurea herbicides belonging to different classes, and to literature data: hypotheses on the existence of preferential degradation pathways are then drawn, in consequence of the molecular structure of the sulfonylurea pesticide. In particular, the use of organic solvents to obtain complete solubilization of the sample plays a fundamental role and deeply influences the degradation processes that, therefore, not always fully adhere to the actual natural photodegradation pathways. Moreover, considerations about toxicity were driven since the complete mineralisation of the sample is not reached: even when the parent pesticides are totally degraded, they are, however, transformed into other organic compounds showing, if subject to ecotoxicological tests, at least the same toxicity of the precursor herbicides. The evidence here presented suggests that, at least for the class of sulfonylurea pesticides, their professed low persistence actually does not produce any real advantage.

Recent progress in developing artificial neural network (ANN) metamodels has paved the way for reliable use of these models in the prediction of air pollutant concentrations in urban atmosphere. However, improvement of prediction performance, proper selection of input parameters and model architecture, and quantification of model uncertainties remain key challenges to their practical use. This study has three main objectives: to select an ensemble of input parameters for ANN metamodels consisting of meteorological variables that are predictable by conventional weather forecast models and variables that properly describe the complex nature of pollutant source conditions in a major city, to optimize the ANN models to achieve the most accurate hourly prediction for a case study (city of Tehran), and to examine a methodology to analyze uncertainties based on ANN and Monte Carlo simulations (MCS). In the current study, the ANNs were constructed to predict criteria pollutants of nitrogen oxides (NOx), nitrogen dioxide (NO2), nitrogen monoxide (NO), ozone (O3), carbon monoxide (CO), and particulate matter with aerodynamic diameter of less than 10 μm (PM10) in Tehran based on the data collected at a monitoring station in the densely populated central area of the city. The best combination of input variables was comprehensively investigated taking into account the predictability of meteorological input variables and the study of model performance, correlation coefficients, and spectral analysis. Among numerous meteorological variables, wind speed, air temperature, relative humidity and wind direction were chosen as input variables for the ANN models. The complex nature of pollutant source conditions was reflected through the use of hour of the day and month of the year as input variables and the development of different models for each day of the week. After that, ANN models were constructed and validated, and a methodology of computing prediction intervals (PI) and probability of exceeding air quality thresholds was developed by combining ANNs and MCSs based on Latin Hypercube Sampling (LHS). The results showed that proper ANN models can be used as reliable metamodels for the prediction of hourly air pollutants in urban environments. High correlations were obtained with R (2) of more than 0.82 between modeled and observed hourly pollutant levels for CO, NOx, NO2, NO, and PM10. However, predicted O3 levels were less accurate. The combined use of ANNs and MCSs seems very promising in analyzing air pollution prediction uncertainties. Replacing deterministic predictions with probabilistic PIs can enhance the reliability of ANN models and provide a means of quantifying prediction uncertainties.

With the filling of the Three Gorges Reservoir, original vegetation in the water level fluctuation zone (WLFZ) between the elevations of 145 and 175 m disappeared due to the reversal of submergence time (winter flooding) and prolonged inundation duration (nearly half a year). To better understand the relationships between the environmental factors and recovered plant communities for reconstructing floristically diverse riparian zone, we conducted a field survey in 11 sites in the WLFZ in June 2010, and vegetation composition, flooding characteristics, heavy metals, and soil major nutrients were determined. Consequently, the canonical correspondence analysis was used to investigate the relationships between plant species composition and flooding characteristics, heavy metal contamination, and soil nutrients. Results demonstrated that vegetation in the WLFZ was dominated by annuals, i.e., Echinochloa crusgalli and Bidens tripartita, and perennials including Cynodon dactylon, and plant species richness and diversity were negatively associated with flooding duration, heavy metal contamination, and nutrients including total phosphorus, available phosphorus, available potassium, and nitrate. Our results suggest that plant species, recovering mainly through soil seed bank and regeneration of remnant individuals, have been influenced by the combined effects of environmental factors.

The aqueous environmental fate of two antibiotics, lincomycin and clarithromycin, and an antiepileptic drug, carbamazepine, was investigated by monitoring drugs decomposition and identifying intermediates in Po river water (North Italy). Initially, control experiments in the dark and under illumination were performed on river water spiked with drugs to simulate all possible transformation processes occurring in the aquatic system. Under illumination, these pharmaceuticals were degraded and transformed into numerous organic intermediate compounds. Several species were formed and characterised by analysing MS and MS ⁿ spectra and by comparison with parent molecule fragmentation pathways. River water was sampled at three sampling points in an urban area. The selected pharmaceuticals were detected in all samples. Eight transformation products identified in the laboratory simulation were found in natural river water from carbamazepine degradation, three from clarithromycin and two from lincomycin. Their transformation occurring in aquatic system mainly involved mono- and poly-hydroxylation followed by oxidation of the hydroxyl groups.