In this paper, bootstrapped wavelet neural network (BWNN) was developed for predicting monthly ammonia nitrogen (NH⁴⁺–N) and dissolved oxygen (DO) in Harbin region, northeast of China. The Morlet wavelet basis function (WBF) was employed as a nonlinear activation function of traditional three-layer artificial neural network (ANN) structure. Prediction intervals (PI) were constructed according to the calculated uncertainties from the model structure and data noise. Performance of BWNN model was also compared with four different models: traditional ANN, WNN, bootstrapped ANN, and autoregressive integrated moving average model. The results showed that BWNN could handle the severely fluctuating and non-seasonal time series data of water quality, and it produced better performance than the other four models. The uncertainty from data noise was smaller than that from the model structure for NH⁴⁺–N; conversely, the uncertainty from data noise was larger for DO series. Besides, total uncertainties in the low-flow period were the biggest due to complicated processes during the freeze-up period of the Songhua River. Further, a data missing–refilling scheme was designed, and better performances of BWNNs for structural data missing (SD) were observed than incidental data missing (ID). For both ID and SD, temporal method was satisfactory for filling NH⁴⁺–N series, whereas spatial imputation was fit for DO series. This filling BWNN forecasting method was applied to other areas suffering “real” data missing, and the results demonstrated its efficiency. Thus, the methods introduced here will help managers to obtain informed decisions.

A large number of bacteria, including agents responsible for diseases, characterise sewage-polluted seawaters. Apart from standards for bathing waters and bivalve aquaculture waters, there are no general microbiological standards applicable to seawaters to help decide if bacterial pollution is within acceptable ranges. This study represents an attempt towards the issue of comparing the susceptibility of different marine invertebrates subjected to polluted seawater with a high microbial contamination. We explored the survival rates and the microbiological accumulation of mollusc bivalves, echinoderms and crustaceans species exposed to sewage-polluted seawaters. Microbiological analyses were performed on the polluted seawater and on the homogenates of exposed and unexposed specimens. Culturable bacteria (22 °C and 37 °C) and microbial pollution indicators (total coliforms, Escherichia coli and intestinal enterococci) were measured. When exposed to the sewage-polluted seawater, the examined invertebrates showed different survival rates. In the filter feeders, bacterial densities at 22 °C and 37 °C rose after 96 h of exposure to sewage. The highest concentrations of total coliforms and intestinal enterococci were found in exposed bivalve Mytilus galloprovincialis. The concentrations of bacteria growing at 37 °C were lower in the exposed deposit feeders compared to the polluted seawater. Some yeasts were absent in several exposed species although these yeasts were present in the polluted seawater. Our data suggest that the examined filter feeders, given their capability to survive and accumulate bacteria, may counteract the effects of sewage and restore seawater quality.

A factory in Amman Garh near Nowshera, Khyber Pakhtunkhwa, Pakistan, produced dichlorodiphenyltrichloroethane (DDT) from 1963–1994. Consequently, earlier papers reported a soil contamination in the per mille range inside the former factory wall (88 m × 106 m) and up to 10 mg/kg of DDT in the surroundings in 2005–2007. The site within the factory wall was remonitored systematically in 2011 to complement the earlier data as a prerequisite for remediation, to put them in exposure context in a population developing area, and to suggest and evaluate the optimal remediation technique for the site. The contamination was drastically higher than the earlier published data, and the sum of DDT and its metabolites (ΣDDT) was up to 65 % in the soil. Grasses, shrubs, and trees growing in this severely contaminated site had 50–450 mg/kgdw of ΣDDT. Thus, people living nearby and husbandry as well as wild animals are heavily exposed to DDT. The semiarid climate favors wind drift and deposition of the pollutant. Additionally, DDT from products of herbivore animals feeding on the contaminated plants will enter the food web. To overcome the exposure and distribution of the DDT, the site within the factory wall was capped with 1.5 m of soil. This remediation technique represents the easiest and least expensive solution. Nevertheless, DDT can still evaporate or leach, and groundwater can rise in this flood-prone area and thereby become contaminated, especially because a binding layer is missing.

The addition of organic matter in soil can modify the bioavailability of heavy metals. A greenhouse pot experiment was carried out using an edible plant species Eruca vesicaria L. Cavalieri grown on an artificially contaminated soil with Zn (665 mg kg(-1)). In this study, the effect of compost at 20 t ha(-1) (C20) and at 60 t ha(-1) (C60), manure at 10 t ha(-1) (M10) and at 30 t ha(-1) (M30), and chemical fertilizers (NPK) on Zn fate in a soil-plant system was evaluated. At the end of the experiment, the main growth parameters and Zn content in plants were determined. In addition, Zn speciation in the soil was assessed using the original Community Bureau of Reference sequential extraction and diethylene triamine pentaacetic acid extraction. Zinc, though an essential element for plant growth, caused toxicity effects in plants grown on control and manure treatments, while in the compost treatments, plants showed no visual toxicity symptoms. The concentrations of Zn in roots were similar for all treatments, while significant differences were observed for shoots. In fact, in the compost treatments, plants showed the lowest Zn concentration in shoots. Zinc speciation seems not to be affected by the applied treatments. Indeed, Zn plant content and translocation to shoots seems to be affected. Compost amendments significantly reduced Zn content and translocation in comparison to other treatments.

There is evidence that over the last 30 years, there have been mass declines in diverse geographic locations among amphibian populations due to disease outbreaks. Multiple causes have been suggested to explain this increase in disease incidence. Among these, climate changes, environmental pollution and reduced water quality are gaining attention. Indeed, some chemicals of environmental concerns are known to alter the immune system. It is possible that exposure to these pollutants could alter the immune system of anurans and render them more susceptible to different pathogens. In this study, we sampled Rana pipiens in five different sites near St. Lawrence River (Quebec, Canada) during the months of July and September in 2001. Two of these sites were protected areas, in which low levels of pesticides were detected, while the remaining three sites were located in areas with intensive corn and soybeans cultivations. Our results demonstrated that frogs living in agricultural regions are smaller in size and weight than frogs living in areas with lower levels of pesticides at both sampling times. Moreover, we have observed a significant decrease in the number of splenocytes (cellularity) and the phagocytic activity in frogs sampled in impacted sites. Taken together, these results suggest that frogs living in agricultural regions might be more vulnerable to infections and diseases through their smaller size and alteration of their immune system. Our results also contribute to the overall discussion on factors involved in amphibian declines.

In 1997, the Polychlorinated dibenzo-para-dioxin (PCDD)/Polychlorinated dibenzofuran (PCDF) concentrations in dairy products in Germany and other European countries increased. The PCDD/PCDF source was contaminated lime used in Brazilian citrus pulp pellets. The contaminated lime was mined from an industrial dump site. However, the detailed origin of the PCDD/PCDFs in the lime was not revealed. This paper investigates the contamination origin and describes the link between lime milk from the dumpsite of a chlorine/organochlorine industry and the contaminated lime. The contaminated lime stem from mining at the corporate landfill of Solvay Indupa in Sao Paulo. The landfill was used for 40 years for deposition of production residues and closed in 1996. The factory operated/operates at least two processes with potentially high PCDD/PCDFs releases namely the oxychlorination process for production of ethylene dichloride (EDC) and the chlor-alkali process. The main landfilled waste was lime milk (1.4 million tons) from the vinyl chloride monomer production (via the acetylene process) along with residues from other processes. The PCDD/PCDF fingerprint revealed that most samples from the chemical landfill showed an EDC PCDD/PCDF pattern with a characteristic octachlorodibenzofuran dominance. The PCDD/PCDF pattern of a Rio Grande sediment samples downstream the facility showed a chlor-alkali pattern with a minor impact of the EDC pattern. The case highlights that PCDD/PCDF- and persistent organic pollutants-contaminated sites need to be identified in a comprehensive manner as required by the Stockholm Convention (article 6) and controlled for their impact on the environment and human health. Landfill mining and reuse of materials from contaminated deposits should be prohibited.

In arid regions, primary pollutants may contribute to the increase of ozone levels and cause negative effects on biotic health. This study investigates the use of adaptive neuro-fuzzy inference system (ANFIS) for ozone prediction. The initial fuzzy inference system is developed by using fuzzy C-means (FCM) and subtractive clustering (SC) algorithms, which determines the important rules, increases generalization capability of the fuzzy inference system, reduces computational needs, and ensures speedy model development. The study area is located in the Empty Quarter of Saudi Arabia, which is considered as a source of huge potential for oil and gas field development. The developed clustering algorithm-based ANFIS model used meteorological data and derived meteorological data, along with NO and NO₂ concentrations and their transformations, as inputs. The root mean square error and Willmott’s index of agreement of the FCM- and SC-based ANFIS models are 3.5 ppbv and 0.99, and 8.9 ppbv and 0.95, respectively. Based on the analysis of the performance measures and regression error characteristic curves, it is concluded that the FCM-based ANFIS model outperforms the SC-based ANFIS model.

While phytoextraction tools are increasingly applied to remediation of contaminated soils, strategies are needed to optimize plant uptake by improving soil conditions. Mineral nutrition affects plant growth and metal absorption and subsequently the accumulation of heavy metal through hyper-accumulator plants. Microcosm experiments were conducted in greenhouse to examine the effect of different phosphorus (P) sources on zinc (Zn) phytoextraction by Sedum alfredii in aged Zn-contaminated paddy soil. The Zn accumulation, soil pH, microbial biomass and enzyme activity, available Zn changes. and Zn phytoremediation efficiency in soil after plant harvest were determined. Upon addition of P, Zn uptake of S. alfredii significantly increased. Mehlich-3 extractable or the fractions of exchangeable and carbonate-bound soil Zn were significantly increased at higher P applications. Soil pH significantly decreased with increasing P application rates. Soil microbial biomass in the P-treated soils was significantly higher (P < 0.05) than those in the control. Shoot Zn concentration was positively correlated with Mehlich-3 extractable P (P < 0.0001) or exchangeable/carbonate-bound Zn (P < 0.001), but negatively related to soil pH (P < 0.0001). These results indicate that application of P fertilizers has the potential to enhance Zn mobility and uptake by hyperaccumulating plant S. alfredii, thus increasing phytoremediation efficiency of Zn-contaminated soils.

Dried sugar beet pulp, an agricultural solid waste, was used for the production of carbon. Carbonised beet pulp was tested in the adsorption of Remazol Black B dye, and adsorption studies with real textile wastewater were also performed. Batch kinetic studies showed that an equilibrium time of 180 min was needed for the adsorption. The maximum dye adsorption capacity was obtained as 80.0 mg g⁻¹ at the temperature of 25 °C at pH = 1.0. The Langmuir and Freundlich adsorption models were used for the mathematical description of the adsorption equilibrium, and it was reported that experimental data fitted very well to the Langmuir model. Mass transfer and kinetic models were applied to the experimental data to examine the mechanisms of adsorption and potential rate-controlling steps. It was found that both external mass transfer and intraparticle diffusion played an important role in the adsorption mechanisms of dye, and adsorption kinetics followed the pseudo-second-order type kinetic model. The thermodynamic analysis indicated that the sorption process was exothermic and spontaneous in nature.

Since the 1990s, the Lake Maggiore (Northern Italy) has been recognized as an aquatic environment contaminated by DDTs and other persistent organic pollutants, but to date just few studies were carried out to investigate the effects of pollution to aquatic organisms. The aim of this study was the application of a stepwise approach based on chemical data, a suite of biomarkers and the integration of their responses into a biomarker response index (BRI) to evaluate the site-specific quality assessment in different sampling stations of Lake Maggiore, one of the largest European lakes. We used as biological model the freshwater bivalve Zebra mussel (Dreissena polymorpha). Several hundred bivalve specimens were sampled on May 2011 from eight sampling sites located along the lake shoreline. We measured levels of DDTs, PCBs, HCHs, HCB, and PAHs accumulated in D. polymorpha soft tissues by GC/MSn, while the activities of catalase, superoxide dismutase, glutathione peroxidase, and glutathione S-transferase, as well as the lipid peroxidation and protein carbonyl content were evaluated in homogenates from native bivalves as oxidative stress indices. Moreover, DNA damage was investigated by the alkaline precipitation assay. Significant imbalances of enzymatic activity were found in mussels from most of the sampling sites, as well as notable increases of damage to macromolecules. Health status of mussels from Baveno was greatly affected by lake pollution, probably due to high levels of DDTs measured in this site, while a wide variability in biomarker responses was found in all the other stations. The application of a BRI allowed distinguishing impacts of pollution to bivalves, confirming mussels from Baveno as the most threatened and revealing that also the health status of bivalves from Suna, Brissago, Pallanza, and Laveno is affected. These evidences suggest the usefulness of a specific index to integrate all the biomarker endpoints in order to provide a correct environmental risk assessment.