The photodegradation processes of fenpropathrin and λ-cyhalothrin were studied in hexane, methanol/water (1:1, v/v), and acetone in both ultraviolet light and simulated sunlight. Intermediates in the photodegradation process were identified using gas chromatography/mass spectrometry (GC/MS), and the analysis of intermediates was used to speculate on possible photodegradation pathways. The photodegradation processes of fenpropathrin and λ-cyhalothrin followed pseudo first-order kinetics. The photodegradation rates varied according to the solvent in decreasing order: hexane > methanol/water (1:1, v/v) > acetone. The effects of substances coexisting in the environment on the photodegradation of pyrethroids were also investigated in the research. Acetone, humic acid, and riboflavin increased photodegradation rates while L-ascorbic acid slowed the process. This study provides a theoretical basis for the removal of pyrethroid pollution from the natural environment.

Birth weight may be influenced by environmental and socio-economic factors that could interact. The main objective of our research was to investigate whether area deprivation may modify the association between drinking water exposure to a mixture of atrazine metabolites and nitrates during the second trimester of pregnancy and prevalence of small for gestational age (SGA) neonates. We conducted a historic cohort study in Deux-Sèvres, France between 2005 and 2010, using birth records, population census and regularly performed drinking water withdrawals at community water systems. Exposure to an atrazine metabolite/nitrate mixture in drinking water was divided into six classes according to the presence or absence of atrazine metabolites and to the terciles of nitrate concentrations in each trimester of pregnancy. We used a logistic regression to model the association between SGA and mixture exposure at the second trimester while taking into account the area deprivation measured by the Townsend index as an effect modifier and controlling for the usual confounders. We included 10,784 woman–neonate couples. The risk of SGA when exposed to second tercile of nitrate without atrazine metabolites was significantly greater in women living in less deprived areas (OR = 2.99; 95 % CI (1.14, 7.89)), whereas it was not significant in moderately and more deprived areas. One of the arguments used to explain this result is the presence of competing risk factors in poorer districts.

This study investigates the occurrence of carbonyl compounds in rainwater at the city of Thessaloniki, Northern Greece. The concentrations of carbonyl compounds (as sum of 14 compounds) ranged from 21.8 to 592 μg/L, mean concentration 119 μg/L. Formaldehyde, acetaldehyde, hexanal, glyoxal, and methylglyoxal were the dominant compounds. DOC concentrations in rainwater ranged from 0.46 to 21.3 mg/L. UV–Vis and fluorescence spectra characteristics showed variation among rain events. Carbonyl compounds were negatively correlated with temperature exhibited relatively higher concentrations in cold season. They also influenced by storm origin with higher concentrations under terrestrial air masses. Calm conditions enhance the concentrations of DOC. Wash out is an effective removal mechanism of DOC.

Displacement of lindane presorbed on the pristine and OH-functionalized multiwalled carbon nanotubes (MWCNTs) by phenanthrene, naphthalene, and atrazine, and competition of these compounds with lindane on the aforementioned sorbents were investigated. Displacement of lindane presorbed on MWCNTs by atrazine, naphthalene, and phenanthrene, and competitive sorption effect of these chemicals with lindane on MWCNTs followed the same order: atrazine > naphthalene > phenanthrene. The lowest competition and displacement of lindane by phenanthrene were mainly because of the strong interactions between these two chemicals, whereas interaction of lindane with atrazine and naphthalene was quite low. The more pronounced displacement of lindane by atrazine than naphthalene and higher competitive sorption of lindane with atrazine than with naphthalene can be ascribed to the larger molecular volume of atrazine; thus, the steric hindrance effect is higher relative to naphthalene. This study is valuable for evaluating influence of the coexisting organic compounds on sorption of primary solute towards MWCNTs in the environment.

Simple and effective extraction methods based on matrix solid-phase dispersion (MSPD), dispersive liquid–liquid microextraction (DLLME), and solid-phase extraction (SPE) coupled with high-performance liquid chromatography with diode array detector (HPLC-DAD) were developed to determine triketone herbicides—sulcotrione (SUL), mesotrione (MES), tembotrione (TEMB), and their degradation products—in plant tissues and water samples. The extraction procedures were employed to enable quantification of the accumulation of selected triketone herbicides and their degradation products in a model aquatic plant, Egeria densa. To obtain comprehensive information about the triketones' influence on an aquatic plant, changes in chlorophyll concentration in plants exposed to these triketones were monitored. The average recovery ranged from 58 to 115 % (coefficients of variation 7–12 %) for plant tissues and from 52 to 96 % (coefficients of variation 8–20 %) for water samples. The limit of detection (LOD) for the MSPD–HPLC-DAD procedure was in the range of 0.06–0.23 μg/g, whereas for DLLME–HPLC-DAD and SPE–HPLC-DAD, LOD was in the range of 0.06–0.26 μg/mL. Symptoms of the phytotoxicity of sulcotrione, mesotrione, tembotrione, and their degradation products (decrease of chlorophyll concentration in plant sprouts) were observed for E. densa cultivated in water with herbicide concentrations of 100 μg/L. Moreover, the tembotrione degradation product exhibited a high level of accumulation and low metabolism in plant tissues in comparison to the other triketones and their degradation products.

In order to examine whether the leaves of the Colorado blue spruce (Picea pungens) are damaged or not by traffic pollution, the traits of the anatomy and physiology of its leaves are investigated by exposure to vehicle exhausts in a laboratory experiment lasting 30 days. The results show that both the anatomical structures and physiological traits of the leaves are significantly affected by vehicle exhausts. The anatomical structures, including epidermis, cuticle, palisade, and spongy parenchyma are modified when exposed to the high concentrations (≥0.4 mg/m³) of vehicle exhausts. However, physiological traits such as total chlorophyll content are not changed when exposed to different concentrations of vehicle exhaust. Unlike the total chlorophyll content, the electrical conductivities increased, whereas the POD activities decreased when presented in vehicle exhausts. The present study indicates that the Colorado blue spruce changes its anatomical structures and physiological traits to avoid possible damage by vehicle exhausts.

This study aims to investigate the influence of the coexistence of halogen ions (bromide/iodide) and biological source matters on the speciation and yield of trihalomethanes (THMs), haloacetic acids (HAAs), and N-nitrosodimethylamine (NDMA) during the ozonation and subsequent chlorination of water. The results show that the concentrations of brominated THMs and iodinated THMs increased with increasing bromide and iodide concentration. These results may be attributed to the higher reactivity of hypobromous acid and hypoiodous acid generated from the ozonation and subsequent chlorination in the presence of bromide or iodide ions. The presence of bromide increased the species of brominated HAAs. There was a shift from chlorinated HAAs to brominated HAAs after increasing the concentration of bromide. The effect of iodide on HAA formation was more complex than bromide. For most samples, the concentration of total HAAs (T-HAAs) increased to the maximum and then decreased with increasing iodide concentration. The components of the organic precursors also significantly influenced the formation of brominated and iodinated disinfection by-products (Br-DBPs and I-DBPs). Humic acids produced more CHBr₃(596.60 μg/L) than other organic materials. Microcystis aeruginosa cells produced the most tribromoacetic acid (TBAA, 84.16 μg/L). Furthermore, the yield of NDMA decreased with increasing bromide concentration, indicating that the formation of NDMA was inhibited by the high concentration of bromide.

Pharmaceuticals and other anthropogenic trace contaminants reach wastewaters and are often not satisfactorily eliminated in sewage treatment plants. These contaminants and/or their degradation products may reach surface waters, thus influencing aquatic life. In this study, the behavior of five different antihypertonic pharmaceuticals from the sartan group (candesartan, eprosartan, irbesartan, olmesartan and valsartan) is investigated in lab-scale sewage plants. The elimination of the substances with related structures varied broadly from 17 % for olmesartan up to 96 % for valsartan. Monitoring data for these drugs in wastewater effluents of six different sewage treatment plants (STPs) in Bavaria, and at eight rivers, showed median concentrations for, e.g. valsartan of 1.1 and 0.13 μg L⁻¹, respectively. Predicted environmental concentrations (PEC) were calculated and are mostly consistent with the measured environmental concentrations (MEC). The selected sartans and the mixture of the five sartans showed no ecotoxic effects on aquatic organisms in relevant concentrations. Nevertheless, the occurrence of pharmaceuticals in the environment should be reduced to minimize the risk of their distribution in surface waters, ground waters and bank filtrates used for drinking water.

The global olive oil production for 2010 is estimated to be 2,881,500 metric tons. The European Union countries produce 78.5 % of the total olive oil, which stands for an average production of 2,136,000 tons. The worldwide consumption of olive oil increased of 78 % between 1990 and 2010. The increase in olive oil production implies a proportional increase in olive mill wastes. As a consequence of such increasing trend, olive mills are facing severe environmental problems due to lack of feasible and/or cost-effective solutions to olive-mill waste management. Therefore, immediate attention is required to find a proper way of management to deal with olive mill waste materials in order to minimize environmental pollution and associated health risks. One of the interesting uses of solid wastes generated from olive mills is to convert them as inexpensive adsorbents for water pollution control. In this review paper, an extensive list of adsorbents (prepared by utilizing different types of olive mill solid waste materials) from vast literature has been compiled, and their adsorption capacities for various aquatic pollutants removal are presented. Different physicochemical methods that have been used to convert olive mill solid wastes into efficient adsorbents have also been discussed. Characterization of olive-based adsorbents and adsorption mechanisms of various aquatic pollutants on these developed olive-based adsorbents have also been discussed in detail. Conclusions have been drawn from the literature reviewed, and suggestions for future research are proposed.

In this study, we present application of an artificial intelligence (AI) technique model called dynamic evolving neural-fuzzy inference system (DENFIS) based on an evolving clustering method (ECM), for modelling dissolved oxygen concentration in a river. To demonstrate the forecasting capability of DENFIS, a one year period from 1 January 2009 to 30 December 2009, of hourly experimental water quality data collected by the United States Geological Survey (USGS Station No: 420853121505500) station at Klamath River at Miller Island Boat Ramp, OR, USA, were used for model development. Two DENFIS-based models are presented and compared. The two DENFIS systems are: (1) offline-based system named DENFIS-OF, and (2) online-based system, named DENFIS-ON. The input variables used for the two models are water pH, temperature, specific conductance, and sensor depth. The performances of the models are evaluated using root mean square errors (RMSE), mean absolute error (MAE), Willmott index of agreement (d) and correlation coefficient (CC) statistics. The lowest root mean square error and highest correlation coefficient values were obtained with the DENFIS-ON method. The results obtained with DENFIS models are compared with linear (multiple linear regression, MLR) and nonlinear (multi-layer perceptron neural networks, MLPNN) methods. This study demonstrates that DENFIS-ON investigated herein outperforms all the proposed techniques for DO modelling.