Exogenously applied calcium alleviates cadmium toxicity in Matricaria chamomilla L. plants

Cadmium (Cd) toxicity in plants leads to serious disturbances of physiological processes, such as inhibition of chlorophyll synthesis, oxidative injury to the plant cells and water and nutrient uptake. Response of Matricaria chamomilla L. to calcium chloride (CaCl₂) enrichment in growth medium for reducing Cd toxicity were studied in this study. Hydroponically cultured seedlings were treated with 0, 0.1, 1, and 5 mM CaCl₂, under 0, 120, and 180 μM CdCl₂ conditions, respectively. The study included measurements pertaining to physiological attributes such as growth parameters, Cd concentration and translocation, oxidative stress, and accumulation of phenolics. Addition of CaCl₂ to growth media decreased the Cd concentration, activity of antioxidant enzymes, and reactive oxygen species accumulation in the plants treated with different CdCl₂, but increased the growth parameters. Malondialdehyde and total phenolics in shoots and roots were not much affected when plants were treated only with different CaCl₂ levels, but it showed a rapid increase when the plants were exposed to 120 and 180 CdCl₂ levels. CaCl₂ amendment also ameliorated the CdCl₂-induced stress by reducing oxidative injury. The beneficial effects of CaCl₂ in ameliorating CdCl₂ toxicity can be attributed to the Ca-induced reduction of Cd concentration, by reducing the cell-surface negativity and competing for Cd²⁺ ion influx, activity enhancement of antioxidant enzymes, and biomass accumulation.     

Predicting hourly air pollutant levels using artificial neural networks coupled with uncertainty analysis by Monte Carlo simulations

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 (NO_x), 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, NO_x, 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.     

Emergy-based fuzzy optimization approach for water reuse in an eco-industrial park

The establishment of an eco-industrial park (EIP) provides opportunity for individual plants to cooperate with each other in order to utilize resources efficiently and thus reduce waste. The goal of an EIP is to “close the loop” through recycling and reuse of material and energy streams. Studies show with current freshwater consumption trends there would be water stress aggravated by global warming in the near future. This paper presents a model to design an EIP water reuse network that considers overall system sustainability as measured with emergy, as well as cost saving desired by individual plants. Case studies from literature are then solved to illustrate the advantage of this method in decision making. The illustrative examples show how the model achieves a compromise among the potentially conflicting fuzzy goals of the various EIP stakeholders.     

Household waste behaviours among a community sample in Iran: An application of the theory of planned behaviour

Understanding the factors influencing recycling behaviour can lead to better and more effective recycling programs in a community. The goal of this study was to examine factors associated with household waste behaviours in the context of the theory of planned behaviour (TPB) among a community sample of Iranians that included data collection at time 1 and at follow-up one year later at time 2. Study participants were sampled from households under the coverage of eight urban health centers in the city of Qazvin. Of 2000 invited households, 1782 agreed to participate in the study. A self-reported questionnaire was used for assessing socio-demographic factors and the TPB constructs (i.e. attitude, subjective norms, perceived behavioural control, and intention). Furthermore, questions regarding moral obligation, self-identity, action planning, and past recycling behaviour were asked, creating an extended TPB. At time 2, participants were asked to complete a follow-up questionnaire on self-reported recycling behaviours. All TPB constructs had positive and significant correlations with each other. Recycling behaviour at time 1 (past behaviour) significantly related to household waste behaviour at time 2. The extended TPB explained 47% of the variance in household waste behaviour at time 2. Attitude, perceived behavioural control, intention, moral obligation, self-identity, action planning, and past recycling behaviour were significant predictors of household waste behaviour at time 2 in all models. The fact that the expanded TPB constructs significantly predicted household waste behaviours holds great promise for developing effective public campaigns and behaviour-changing interventions in a region where overall rates of household waste reduction behaviours are low. Our results indicate that educational materials which target moral obligation and action planning may be particularly effective.     

Mercury speciation in the Persian Gulf sediments

The concentrations of total mercury (Hg) and methyl mercury (MMHg) were determined in 78 marine sediments in the Iranian coastal waters of the Persian Gulf along nine transects perpendicular to the coastline. Total Hg ranged from 10 to 56 ng g( - 1)d.w. and MMHg from 0.1 to 0.4 ng g( - 1) d.w. The fraction of methyl mercury accounted from 0.3% to 1.1% of the total mercury amount. The organic carbon (OC) content ranged from 0.4% to 1.8%. The present study indicates that the levels of Hg in the sediments of the Iranian coast of the Persian Gulf were all in the concentration range of unpolluted areas regarding Hg (<100 ng g( - 1)). The concentrations of total Hg, methyl mercury and organic carbon were generally higher in the deeper stations. Total Hg and MMHg were significantly correlated, but no significant correlations could be found between the Hg and OC levels.     

A simple method for simultaneous determination of some organic liquids in in-process materials and effluents produced in the manufacture of amoxicillin and ampicillin

A simple GC method for simultaneous determination of pivaloylchloride, methylacetoacetate, ethylacetoacetate and 2-ethylhexanoic acid in the presence of each other has been developed using glass column packed with 1% Silicone OV-17 on Gaschrom Q 100-120 mesh with temperature programming. Various performance parameters including precision, linearity and limit of detection have been evaluated. The method was found to be suitable for the analysis of these chemicals in in-process materials and effluents associated with the manufacture of amoxicillin and ampicillin. The run time was less than 15 min. The method has been successfully applied to determine the level of these hazardous organic liquids in real time samples.     

Design based estimation for ranked set sampling in finite populations

In this paper, we consider design-based estimation using ranked set sampling (RSS) in finite populations. We first derive the first and second-order inclusion probabilities for an RSS design and present two Horvitz–Thompson type estimators using these inclusion probabilities. We also develop an alternate Hansen–Hurwitz type estimator and investigate its properties. In particular, we show that this alternate estimator always outperforms the usual Hansen–Hurwitz type estimator in the simple random sampling with replacement design with comparable sample size. We also develop formulae for ratio estimator for all three developed estimators. The theoretical results are augmented by numerical and simulation studies as well as a case study using a well known data set. These show that RSS design can yield a substantial improvement in efficiency over the usual simple random sampling design in finite populations.     

The level and distribution of selected organochlorine pesticides in sediments from River Chenab,Pakistan

Organochlorine pesticides (OCPs), viz. β-hexachlorocyclohexane (β-HCH), γ-HCH, aldrin, dieldrin, endrin, heptachlor, endosulfan-I, endosulfan-II, heptachlor endoepoxide, heptachlor exoepoxide, mirex, dicofol, o,p′-dichlorodiphenyltrichloroethane (o,p′-DDT), p,p′-dichlorodiphenyltrichloroethane (p,p′-DDT), dichlorodiphenyldichloroethane (DDD), and dichlorodiphenyltrichloroethylene (DDE) and 12 other physicochemical parameters were measured in surface sediments from River Chenab during two sampling seasons (summer and winter, 2007) to evaluate spatial and temporal trends of sediment pollution. Hierarchical agglomerative cluster analysis identified three groups of sites based on spatial similarities in physicochemical parameters and OCP residual concentrations. Spatial discriminant function analysis (DFA) segregated 14 parameters, viz. dicofol, endosulfan-I, heptachlor endoepoxide, dieldrin, DDD, DDE, endosulfan-II, o,p′-DDT, p,p′-DDT, pH, electrical conductivity (EC), Cl⁻¹, total P (%), and silt, which explained 96% of total variance between spatial groups. γ-HCH was the most frequently detected (63%) pesticide, followed by DDD (56%). The ratio of DDTs to their metabolites indicated current input and anaerobic biodegradation. Temporal DFA highlighted aldrin, heptachlor endoepoxide, Cl⁻¹, total P, and EC as important variables which caused variations between summer and winter. DDTs were relatively more prevalent as compared to other OCPs in the sediments samples during both seasons. DDT metabolites were detected at greater frequencies and concentrations in winter, whereas DDT isomers were more prevalent in summer sediment samples. Factor analysis identified agricultural and industrial activities as major sources of sediment OCP contamination. Concentrations of γ-HCH, heptachlor endoepoxide, dieldrin, and DDTs (isomers and metabolites) in all sediment samples were well above interim sediment quality guidelines (ISQGs) and probable effect limits (PEL) given by Canadian Sediment Quality Guidelines (CSQGs).     

Determination of nickel, copper, zinc and lead in human scalp hair in Syrian occupationally exposed workers by total reflection X-ray fluorescence

In this study, an attempt has been made to study methane flux and quantification of heavy metals from Municipal Solid Waste (MSW) landfill areas of selected cities in India. During the period of study, the average value of methane flux was estimated from these landfill areas varied from 146–454 mg/m2/h. Methane emission from landfill is of serious environmental global concern as it accounts for approximately 15 percentages of current Greenhouse gas emissions. It has been estimated that methane emission, from landfill areas in the world, in next two decades would be same as that what is emitted from paddy fields presently. Besides, the estimation of methane flux, quantification of some heavy metals was conducted to analyse the suitability of using MSW as compost. The average values for metals were observed to be both within the range of USEPA and Indian standards for MSW disposal in landfill areas and to be used as compost respectively.     

Evaluation of Pb, Cu, Zn, Cd, Ni and Fe levels in Rosmarinus officinalis labaiatae (Rosemary) medicinal plant and soils in selected zones in Jordan

The concentration of heavy metals including Pb, Cu, Zn, Cd, Ni and Fe in different parts of Rosmarinus officinalis medicinal plant grown in Jordan were evaluated. Medicinal plant samples and soil samples were collected from three different zones in Jordan (Irbid, Al-Mafraq and Ma’an). Samples were analyzed by atomic absorption spectrometry (AAS) after chemical treatments using acid digestion procedures. Heavy metal levels in washed and unwashed in each part of R. officinalis were analyzed and compared statistically. Results show that concentrations of investigated heavy metals were varied from plant part to another part of R. officinalis. For example, Pb, Zn, Cu and Cd in most parts of R. officinalis in the three zones were concentrated in the following order: flowers, leaves, stems, whereas Pb, Ni and Fe were concentrated in order as follows: leaves, flowers and stems. Heavy metal concentrations in soil samples was evaluated and correlated with their levels in R. officinalis. Two standard reference materials of plant (SRM 1790a; spinach leaves and CRM 281; rye grass) and one standard reference materials of soil (GBW 07406) were examined to validate the method used. Results show that high recoveries were obtained.