Correction to: Impact of biogas digestates on soil microbiota in agriculture: a review

Environmental Chemistry Letters -     

Low levels of lead and glutathione markers of redox status in human blood

Exposure to lead (Pb) is implicated in a plethora of health threats in both adults and children. Increased exposure levels are associated with oxidative stress in the blood of workers exposed at occupational levels. However, it is not known whether lower Pb exposure levels are related to a shift toward a more oxidized state. To assess the association between blood lead level (BLL) and glutathione (GSH) redox biomarkers in a population of healthy adults, BLL and four GSH markers (GSH, GSSG, GSH/GSSG ratio and redox potential E _h ) were measured in the blood of a cross-sectional cohort of 282 avid seafood-eating healthy adults living on Long Island (NY). Additionally, blood levels of two other metals known to affect GSH redox status, selenium (Se) and mercury (Hg), and omega-3 index were tested for effect modification. Regression models were further adjusted for demographic and smoking status. Increasing exposure to Pb, measured in blood, was not associated with GSSG, but was associated with lower levels of GSH/GSSG ratio and more positive GSH redox potential E _h , driven by its association with GSH. No effect modification was observed in analyses stratified by Hg, Se, omega-3 index, sex, age, or smoking. Blood Pb is associated with lower levels of GSH and the GSH/GSSG ratio in this cross-sectional study of healthy adults.     

Assessment of human health risks and pollution index for heavy metals in farmlands irrigated by effluents of stabilization ponds

Areas contaminated with heavy metals can pose major risks to human health and ecological environments. The aims of this study are to assess human health risk and pollution index for heavy metals in agricultural soils irrigated by effluents of stabilization ponds in Birjand, Iran. The results revealed that the levels of Cr, Mn, Zn, Fe, Cu, Cd, and Pb were in range of 70.3–149.65, 355–570, 31.15–98.45, 23,925–29,140, 22.75–25.95, 0.17–6.51, and 8.5–23.5 mg/kg in topsoils, respectively. Total hazard index values from heavy metals through three exposure routes for adults and children were 9.13E−01 and 1.10, respectively, indicating that there was non-carcinogenic risk for children. The total risk of carcinogenic metals (Cr, Cd, and Pb) through the three exposure routes for adults and children was 1.06E−04 and 9.76E−04, respectively, which indicates that the metals in the soil will not induce carcinogenic risks to these age groups. Pollution levels of heavy metals in soil samples including enrichment factor (EF), contamination factor (CF), pollution load index (PLI), and geo-accumulation index (Igeo) showed heavy metal contamination of agricultural soils. The results of the present study provide basic information about heavy metal contamination control and human health risk assessment management in the study area.     

Characterisation of growth and biochemical response of Onopordum acanthium L. under lead stress as affected by microbial inoculation

Microbial associations may influence the negative effects of potentially toxic elements on plants. In a greenhouse experiment, the growth; biochemical response; and Pb, Fe, and Zn uptake of Onopordum acanthium L. were investigated in response to inoculation with arbuscular mycorrhizal fungi, AMF (a mixture of Funneliformis mosseae, Rhizophagus irregularis, and Rhizophagus fasciculatus) and plant growth-promoting rhizobacteria, PGPR (a mixture of Pseudomonas species including P. putida, P. fluorescens, and P. aeruginosa) at increased Pb levels in soil. The treatments were arranged as a factorial experiment based on a randomised complete block design. Results revealed that inoculation with AMF and PGPR decreased Pb toxicity in plants. Inoculated plants with AMF and PGPR had higher shoot and root dry weight compared with the non-inoculated plants. In this study, AMF and PGPR inoculation led to a significant increase (P?≤?.05) in chlorophyll a, b, chlorophyll a+b, carotenoid, proline, and relative water content of plants. Furthermore, AMF and PGPR inoculation likely played a more important role in growth and Pb uptake in O. acanthium L. Our results suggest that AMF and Pseudomonas bacteria could be effective bio-inoculants for enhancing the plant growth and Pb uptake by inhibiting the adverse effects of Pb in O. acanthium.     

Microbial diversity and ecological networks as indicators of environmental quality

Evaluating the quality of ecosystems in terms of biological patrimony and functioning is of critical importance in the actual context of intensified human activities. Microbial diversity is commonly used as a bioindicator of ecosystems functioning. However, there is a lack of sensitivity of microbial diversity indicators in the case of moderate and chronic environmental degradation, such as atmospheric deposition of pollutants, agricultural practices, diffuse pollution by wastewater and climate change. As a consequence, there is a need for alternative bioindicators of soils and water quality. Here, we discuss the interest of adopting a more integrative approach based on biotic interaction networks beyond the simple diversity indicators. We review how the various biotic interactions can be integrated in the various microbial networks such as trophic, mutualistic and co-occurrence networks. Then we discuss the efficiency of microbial networks and associated metrics to detect changes in microbial communities. We conclude that the connectance, the number of links and the average degree of co-occurrence networks could vary from 10 to 50% in response to minor perturbations when microbial diversity parameters remain stable. Finally, we analyze studies that aimed at linking microbial networks and activity to evaluate the potential of such networks for providing simple and operational indicators of ecosystem quality and functioning.     

Forecasting of daily total atmospheric ozone in Isfahan

A neural network combined to an artificial neural network model is used to forecast daily total atmospheric ozone over Isfahan city in Iran. In this work, in order to forecast the total column ozone over Isfahan, we have examined several neural networks algorithms with different meteorological predictors based on the ozone-meteorological relationships with previous day's ozone value. The meteorological predictors consist of temperatures (dry and dew point) and geopotential heights at standard levels of 100, 50, 30, 20 and 10 hPa with their wind speed and direction. These data together with previous day total ozone forms the input matrix of the neural model that is based on the back propagation algorithm (BPA) structure. The output matrix is the daily total atmospheric ozone. The model was build based on daily data from 1997 to 2004 obtained from Isfahan ozonometric station data. After modeling these data we used 3 year (from 2001 to 2003) of daily total ozone for testing the accuracy of model. In this experiment, with the final neural network, the total ozone are fairly well predicted, with an Agreement Index 76%.     

Selecting the Best Compatible SVC Type in Power Systems for transient Stability

Considering the increased trend to use renewable energy to meet electrical energy demands, a reliable performance also should be adopted in transmitting the generated power through the stable transmission and subtransmission systems for which nowadays Flexible AC Transmission System (FACTS) controllers are used extensively. Transient stability is one of the most important issues in power system stability analysis. FACTS devices have confirmed their capabilities in various aspects in power networks. In this paper, to improve transient stability of power systems, a shunt connected FACTS devices have been introduced, i.e., Static VAR compensators (SVCs). The SVC has the most diversified branches among FACTS devices. The main aim of this work is to study and analyze the impact of eight branches of SVC on improvement of transient stability and to choose the best of them. Simulations are performed in MATLAB/SIMULINK environment.     

A basic neural traffic noise prediction model for Tehran’s roads

We present an artificial neural network model to predict hourly A-weighted equivalent sound pressure levels (L_Aeq,1h) for roads in Tehran at distances less than 4 m from the nearside carriageway edge. Our model uses the UK Calculation of Road Traffic Noise (CORTN) approach. Data were obtained from 50 sampling locations near five roads in Tehran at nearside carriageway edge distances of less than 4 m. The data were randomly assigned to training, testing, and holdout subsets. Model training was carried out using the training and testing subsets and comprised 60% and 20% of the data, respectively. Model validation was performed using the remaining 20% of data as a holdout subset. We examine the overall model efficiency using non-parametric tests, such as the Wilcoxon matched-pairs signed-rank test for the training step and the Kolmogorov–Smirnov test for two independent samples for the validation step. Our results indicate that a neural network approach can be applied for traffic noise prediction in Tehran in a statistically sound manner. The Wilcoxon matched-pairs signed-ranks test detects no significant difference between the absolute testing set errors of the developed neural network and a calibrated version of the CORTN model.     

Euphorbia leaf extract-assisted sustainable synthesis of Au NPs supported on exfoliated GO for superior activity on water purification: reduction of 4-NP and MB

Environmental Science and Pollution Research - In the present work, the effect of graphene oxide (GO) architecture and synthesis of gold nanoparticles (AuNPs) on the surface of GO by using...     

Impact of land disturbance on the fate of arsenical pesticides

Increasing development of historic farmlands raises questions regarding the fate of pesticides applied when these land were in cultivation. We quantified As and Pb budgets in field soils in two orchards where arsenical pesticides were applied in the early 20th century and a third uncontaminated control field. Sequential extractions and X-ray analyses also were used to determine mineral phases. In addition, we measured metal loads in drainages adjacent to the fields and in two common macroinvertebrate taxa within the wetland at the outlet of the drainages. We find that the applied As and Pb have undergone little vertical redistribution; concentrations of As and Pb in the top 25 cm of contaminated orchard soils are higher than in the uncontaminated control field. However, none of the applied lead arsenate (PbHAsO4) remains in its original mineral phase. Instead, the metals are now primarily adsorbed onto fine silt and clay-sized amorphous oxides and organic matter. Further, physical erosion associated with tilling and replanting appears to have mobilized the fine-particulate-bound As and Pb in one orchard. The remobilized metals are found in sediments in the stream channel draining the tilled orchard. It is unclear if the As and Pb transported sediments are biologically active; average macroinvertebrate metal burdens in the wetland are not elevated above those observed elsewhere in the region. However, little of the mobilized metals may have reached the wetland. These results demonstrate that land use change can significantly impact the retention of arsenical pesticides.