Samples of pond sediment, fish, and shrimp were collected from the Ramsar site at Mai Po marshes, Hong Kong (south China), and samples of pond sediment, fish, and shrimp, as well as eggs of water birds (Chinese Pond Herons (Ardeola bacchus) and Little Egrets (Egretta garzetta)), were collected from two smaller wetland sites at Jiangsu Province (mid-China), between 2004 and 2007. Accumulation levels of polycyclic aromatic hydrocarbons (PAHs) and organochlorine pesticides (OCPs) in the biota were used to calculate biota–sediment accumulation factor (BSAF) and bioaccumulation factor (BAF). For fish and shrimp, BSAFs of OCPs (3.8–56) were greater than those of PAHs (0.12–6.3). BSAFs and BAFs of 11–79 and 4–34, respectively, were registered for OCPs in eggs of the birds and were greater than those for PAHs (0.11–1.5 and 0.02–1.3, respectively). Assuming that fish were the main prey of the birds, greater bioaccumulation of OCPs was detected for both bird species (BAFs = 4.5–34), while accumulation of PAHs was only detected in Little Egret (BAF = 1.3). A significant linear relationship (p < 0.01) was observed between concentrations of OCPs in bird eggs and in the prey fish. The present study provides a new possibility of using OCP levels detected in prey fish to predict the extent of OCPs contamination in eggs of waterbirds including the endangered species, as a noninvasive method.

Lead from historical mining and mineral processing activities may pose potential human health risks if materials with high concentrations of bioavailable lead minerals are released to the environment. Since the Joint Expert Committee on Food Additives of Food and Agriculture Organization/World Health Organization withdrew the Provisional Tolerable Weekly Intake of lead in 2011, an alternative method was required for lead exposure assessment. This study evaluated the potential lead hazard to young children (0-7 years) from a historical mining location at a semi-arid area using the U.S. EPA Integrated Exposure Uptake Biokinetic (IEUBK) Model, with selected site-specific input data. This study assessed lead exposure via the inhalation pathway for children living in a location affected by lead mining activities and with specific reference to semi-arid conditions and made comparison with the ingestion pathway by using the physiologically based extraction test for gastro-intestinal simulation. Sensitivity analysis for major IEUBK input parameters was conducted. Three groups of input parameters were classified according to the results of predicted blood concentrations. The modelled lead absorption attributed to the inhalation route was lower than 2 % (mean ± SE, 0.9 % ± 0.1 %) of all lead intake routes and was demonstrated as a less significant exposure pathway to children's blood, compared with ingestion. Whilst dermal exposure was negligible, diet and ingestion of soil and dust were the dominant parameters in terms of children's blood lead prediction. The exposure assessment identified the changing role of dietary intake when house lead loadings varied. Recommendations were also made to conduct comprehensive site-specific human health risk assessment in future studies of lead exposure under a semi-arid climate.

There is extensive evidence of the negative impacts on health linked to the rise of the regional background of particulate matter (PM) 10 levels. These levels are often increased over urban areas becoming one of the main air pollution concerns. This is the case on the Bilbao metropolitan area, Spain. This study describes a data-driven model to diagnose PM10 levels in Bilbao at hourly intervals. The model is built with a training period of 7-year historical data covering different urban environments (inland, city centre and coastal sites). The explanatory variables are quantitative—log [NO₂], temperature, short-wave incoming radiation, wind speed and direction, specific humidity, hour and vehicle intensity—and qualitative—working days/weekends, season (winter/summer), the hour (from 00 to 23 UTC) and precipitation/no precipitation. Three different linear regression models are compared: simple linear regression; linear regression with interaction terms (INT); and linear regression with interaction terms following the Sawa’s Bayesian Information Criteria (INT-BIC). Each type of model is calculated selecting two different periods: the training (it consists of 6 years) and the testing dataset (it consists of 1 year). The results of each type of model show that the INT-BIC-based model (R² = 0.42) is the best. Results were R of 0.65, 0.63 and 0.60 for the city centre, inland and coastal sites, respectively, a level of confidence similar to the state-of-the art methodology. The related error calculated for longer time intervals (monthly or seasonal means) diminished significantly (R of 0.75–0.80 for monthly means and R of 0.80 to 0.98 at seasonally means) with respect to shorter periods.

Intraspecific variation in six cultivars of clover Trifolium alexandrinum L., (Bundel, Wardan, JHB-146, Saidi, Fahli, and Mescavi) has been studied with ambient and elevated O3 (ambient + 10 ppb O3) in open top chambers. Significant effect of elevated O3 was detected on different morphological, physiological, and biochemical parameters depicting differential response among the test cultivars. Results showed that the magnitude of O3 induced foliar injury symptoms varied in all the cultivars. Ozone significantly depressed photosynthetic rate, stomatal conductance, and photosynthetic efficiency, although variations were cultivar specific. Ozone treatment diminished total biomass of all the cultivars; reduction was highest in Wardan with least O3 resistance followed by Bundel, JHB-146, Saidi, Mescavi, and Fahli. According to the cumulative sensitive index, variations in the sensitivity showed that two cultivars (Wardan and Bundel) were sensitive to elevated O3, while other three cultivars (Fahli, Saidi, and Mescavi) were resistant, and JHB-146 showed intermediate sensitivity. Therefore, the present study supported the selection of sensitive cultivar of clover as a bioindicator for O3 under Indian conditions for the areas experiencing higher concentrations of O3.

The concentrations of heavy metals (Cd, Cr, Cu, Ni, Pb, and Zn) and organic carbon in surface sediments, collected from the southern Bohai Bay, were determined to assess the potential contamination and determine the environmental risks associated with heavy metals. Results showed that heavy metal concentrations in the sediments generally met the China Marine Sediment Quality criteria. Both the ecotoxicological index and the potential ecological risk index suggest that the combined ecological risk of the six studied metals may be low, with the highest ecotoxicological potential zones located in the offshore area. The methods of enrichment factor and geoaccumulation index suggested that elevated concentrations of Cd, Cr, and Ni are presented in the region. Multivariate analysis also indicated that the lithogenic factor dominates the distribution of most part of the considered metals in the study area, whereas Cd and Cr are clearly influenced by anthropogenic inputs. The results of this study are likely to be a useful tool to authorities in charge of sustainable marine management.

This study represents a first attempt at applying a fuzzy inference system (FIS) and an adaptive neuro-fuzzy inference system (ANFIS) to the field of aquatic biomonitoring for classification of the dosage and time of benzo[a]pyrene (BaP) injection through selected biomarkers in African catfish (Clarias gariepinus). Fish were injected either intramuscularly (i.m.) or intraperitoneally (i.p.) with BaP. Hepatic glutathione S-transferase (GST) activities, relative visceral fat weights (LSI), and four biliary fluorescent aromatic compounds (FACs) concentrations were used as the inputs in the modeling study. Contradictory rules in FIS and ANFIS models appeared after conversion of bioassay results into human language (rule-based system). A “data trimming” approach was proposed to eliminate the conflicts prior to fuzzification. However, the model produced was relevant only to relatively low exposures to BaP, especially through the i.m. route of exposure. Furthermore, sensitivity analysis was unable to raise the classification rate to an acceptable level. In conclusion, FIS and ANFIS models have limited applications in the field of fish biomarker studies.

Clays such as kaolin, bentonite and zeolite were evaluated as support material for nanoscale zero-valent iron (nZVI) to simultaneously remove Cu²⁺ and Zn²⁺ from aqueous solution. Of the three supported nZVIs, bentonite-supported nZVI (B-nZVI) was most effective in the simultaneous removal of Cu²⁺ and Zn²⁺ from a aqueous solution containing a 100 mg/l of Cu²⁺ and Zn²⁺, where 92.9 % Cu²⁺ and 58.3 % Zn²⁺ were removed. Scanning electronic microscope (SEM) revealed that the aggregation of nZVI decreased as the proportion of bentonite increased due to the good dispersion of nZVI, while energy dispersive spectroscopy (EDS) demonstrated the deposition of copper and zinc on B-nZVI after B-nZVI reacted with Cu²⁺ and Zn²⁺. A kinetics study indicated that removing Cu²⁺ and Zn²⁺ with B-nZVI accorded with the pseudo first-order model. These suggest that simultaneous adsorption of Cu²⁺and Zn²⁺ on bentonite and the degradation of Cu²⁺and Zn²⁺ by nZVI on the bentonite. However, Cu²⁺ removal by B-nZVI was reduced rather than adsorption, while Zn²⁺ removal was main adsorption. Finally, Cu²⁺, Zn²⁺, Ni²⁺, Pb²⁺ and total Cr from various wastewaters were removed by B-nZVI, and reusability of B-nZVI with different treatment was tested, which demonstrates that B-nZVI is a potential material for the removal of heavy metals from wastewaters.

Leaves of linden (Tilia tomentosa L. and Tilia cordata Mill.) and horse chestnut (Aesculus hippocastanum L.) were analysed as biomonitors of radionuclides in urban air. Samples of soils, leaves and aerosols were collected in Belgrade, Serbia. Activities of ¹³⁷Cs, ⁴⁰K, ²¹⁰Pb and ⁷Be in the samples were measured on an HPGe detector by standard gamma spectrometry. “Soil-to-leaves” transfer factors were calculated. Student’s t test and linear Pearson correlation coefficients were used for statistical analysis. Differences in local conditions at the sampling sites were not significant, and the mechanisms of the radionuclides’ accumulation in both plant species are similar. Ceasium-137 was detected in some of the leaf samples only. Transfer factors for ¹³⁷Cs and ⁴⁰K were (0.03–0.08) and 1.3, respectively. The concentrations of ²¹⁰Pb and ⁷Be in leaves were higher in autumn than in spring, and there were some similarities in their seasonal patterns in leaves and in air. Weak to medium correlation was obtained for the ²¹⁰Pb and ⁷Be activities in leaves and aerosols. Large positive correlation was obtained for the ²¹⁰Pb activities in linden leaves and the mean activity in aerosols for the preceding months. Different primary modes of radionuclides accumulation in leaves were observed. Since large positive correlation was obtained for the ²¹⁰Pb activity in linden leaves and the mean in aerosols for the preceding months, mature linden leaves could be used as biomonitors of recent ²¹⁰Pb activity in air.

The adsorption of Pb(II) onto the surface of microwave-assisted activated carbon was studied through a two-layer feedforward neural network. The activated carbon was developed by microwave activation of Acacia auriculiformis scrap wood char. The prepared adsorbent was characterized by using Brunauer–Emmett–Teller (BET) surface area analyzer, scanning electron microscope (SEM), and X-ray difractometer. In the present study, the input variables for the proposed network were solution pH, contact time, initial adsorbate concentration, adsorbent dose and temperature, whereas the output variable was the percent Pb(II) removal. The network had been trained by using different algorithms and based on the lowest mean squared error (MSE) value and validation error, resilient backpropagation algorithm with 12 neurons in the hidden layer was selected for the present investigation. The tan sigmoid and purelin transfer function were used in the hidden and the output layers of the proposed network, respectively. The model predicted and experimental values of the percent Pb(II) removal were also compared and both the values were found to be in reasonable agreement with each other. The performance of the developed network was further improved by normalizing the experimental data set and it was found that after normalization, the MSE and validation error were reduced significantly. The sensitivity analysis was also performed to determine the most significant input parameter.