Environmentally relevant exposures of male mice to carbendazim and thiram cause persistent genotoxicity in male mice

Environmental Science and Pollution Research - Carbendazim and thiram are fungicides used in combination to prevent mold destruction of crops. Studies have demonstrated genotoxicity by these...     

Energy Communication: Theory and Praxis Towards a Sustainable Energy Future

This essay comments and expands upon an emerging area of research, energy communication, that shares with environmental communication the fraught commitment to simultaneously study communication as an ordinary yet potentially transformative practice, and a strategic endeavour to catalyse change. We begin by defining and situating energy communication within ongoing work on the discursive dimensions of energy extraction, production, distribution, and consumption. We then offer three generative directions for future research related to energy transitions as communicative processes: analysing campaigns’ strategic efforts, critically theorizing energy’s transnational power dynamics, and theorizing the energy democracy movement.     

Multi-metal resistance and plant growth promotion potential of a wastewater bacterium Pseudomonas aeruginosa and its synergistic benefits

Water and soil pollution by toxic heavy metals (HMs) is increasing globally because of increase in population, industrialization and urbanization. It is a burning problem for the public, scientists, academicians and politicians how to tackle the toxic contaminants which jeopardize the environment. One possible solution for pollution abatement is a bioremediation-effective and innovative technology that uses biological systems for treatment of contaminants. Many bacteria synthesize indole-3-acetic acid (IAA) which is a product of l-tryptophan metabolism and belongs to the auxin class of plant growth-promoting hormone. The present study aimed at assessing the resistance pattern of wastewater bacteria against multiple HMs and plant growth promotion activity associated with IAA. A Gram-negative bacterial strain Pseudomonas aeruginosa KUJM was isolated from Kalyani Sewage Treatment Plant. This strain showed the potential to tolerate multiple contaminations such as As(III) (50 mM), As(V) (800 mM), Cd (8 mM), Co (18 mM), Cu (7 mM), Cr (2.5 mM), Ni (3 mM) and Zn (14 mM). The capability of IAA production at different tryptophan concentration (1, 2, 5 and 10 mg mL⁻¹) was determined, and seed germination-enhancing potential was also estimated on lentil (Lens culinaris). Such type of HM-resistant, IAA-producing and seed germination-enhancing P. aeruginosa KUJM offer great promise as inoculants to promote plant growth in the presence of toxic HMs, as well as plant inoculant systems useful for phytoremediation of polluted soils. Hence, P. aeruginosa KUJM finds significant applications in HM-contaminated poor agricultural field as well as in bioremediation of HM-contaminated wastewater system.

     

Distribution of Metals in the Edible Plants Grown at Jajmau, Kanpur (India) Receiving Treated Tannery Wastewater: Relation with Physico-Chemical Properties of the Soil

The implications of metal contamination of agricultural soils due to long term irrigation with treated industrial wastewater and their subsequent accumulation in the vegetables/crops growing on such soils has been assessed in an area of industrial complex, Jajmau, Kanpur (India). Physico-chemical properties of the soil were also studied. The soil and vegetables/crops were sampled from an area of 2100 acre agricultural land and analyzed for physico-chemical properties and metal accumulation in different parts of the plants. The comparison of the data of physico-chemical properties of control and contaminated soil showed that salinity, electrical conductivity, available phosphorous, sodium and potassium content (both water soluble and exchangeable) were found high in contaminated soil. The analysis of plant available metal content in the soil showed the highest level of Fe, which ranged from 529.02 to 2615 μg g⁻¹ dw and lowest level of Ni (3.12 to 10.51 μg g⁻¹ dw). The analysis of the results revealed that accumulation of toxic metal Cr in leafy vegetables was found more than fruit bearing vegetables/crops. Thus, it is recommended that the leafy vegetables are unsuitable to grow in such contaminated sites. It is important to note that toxic metal, Ni was not detected in all the plants. The edible part of the vegetables (under ground) such as, garlic (19.27 μg g⁻¹ dw), potato (11.81 μg g⁻¹ dw) and turmeric (20.86 μg g⁻¹ dw) has accumulated lowest level of toxic metal, Cr than leafy and fruit bearing vegetables. In some fruit part of vegetables such as, bitter gourd, egg plant, jack tree, maize and okra, the accumulation of Cr was not detected and may be grown in this area.     

An eco-sustainable green approach for heavy metals management: two case studies of developing industrial region

Multifaceted issues or paradigm of sustainable development should be appropriately addressed in the discipline of environmental management. Pollution of the biosphere with toxic metals has accelerated dramatically since the beginning of the Industrial Revolution. In present review, comparative assessment of traditional chemical technologies and phytoremediation has been reviewed particularly in the context of cost-effectiveness. The potential of phytoremediation and green chemicals in heavy metals management has been described critically. Further, the review explores our work on phytoremediation as green technology during the last 6 years and hand in hand addresses the various ecological issues, benefits and constraints pertaining to heavy metal pollution of aquatic ecosystems and its phytoremediation as first case study. Second case study demonstrates the possible health implications associated with use of metal contaminated wastewater for irrigation in peri-urban areas of developing world. Our researches revealed wetland plants/macrophytes as ideal bio-system for heavy metals removal in terms of both ecology and economy, when compared with chemical treatments. However, there are several constraints or limitations in the use of aquatic plants for phytoremediation in microcosm as well as mesocosm conditions. On the basis of our past researches, an eco-sustainable model has been proposed in order to resolve the certain constraints imposed in two case studies. In relation to future prospect, phytoremediation technology for enhanced heavy metal accumulation is still in embryonic stage and needs more attention in gene manipulation area. Moreover, harvesting and recycling tools needs more extensive research. A multidisciplinary research effort that integrates the work of natural sciences, environmental engineers and policy makers is essential for greater success of green technologies as a potent tool of heavy metals management.     

Occurrence of pharmaceuticals in urban wastewater of north Indian cities and risk assessment

Six pharmaceuticals of different categories, such as nonsteroidal anti-inflammatory drugs (ibuprofen, ketoprofen, naproxen, diclofenac), anti-epileptic (carbamazepine), and anti-microbial (trimethoprim), were investigated in wastewater of the urban areas of Ghaziabad and Lucknow, India. Samples were concentrated by solid phase extraction (SPE) and determined by high-performance liquid chromatography (HPLC) methods. The SPE-HPLC method was validated according to the International Conference on Harmonization guidelines. All the six drugs were detected in wastewater of Ghaziabad, whereas naproxen was not detected in Lucknow wastewater. Results suggest that levels of these detected drugs were relatively higher in Ghaziabad as compared to those in Lucknow, and diclofenac was the most frequently detected drug in both the study areas. Detection of these drugs in wastewater reflects the importance of wastewater inputs as a source of pharmaceuticals. In terms of the regional distribution of compounds in wastewater of two cities, higher spatial variations (coefficient of variation 112.90–459.44 %) were found in the Lucknow wastewater due to poor water exchange ability. In contrast, lower spatial variation (162.38–303.77 %) was observed in Ghaziabad. Statistical analysis results suggest that both data were highly skewed, and populations in two study areas were significantly different (p?NSAIDs) posed high (RQ >1) risk to all the test species. The present study would contribute to the formulation of guidelines for regulation of such emerging pharmaceutical contaminants in the environment.     

Heavy metals in water, sediments and wetland plants in an aquatic ecosystem of tropical industrial region, India

Concentrations of heavy metals (Cu, Cr, Fe, Pb, Zn, Hg, Ni, and Cd) and macronutrients (Mn) were measured in industrial effluents, water, bottom sediments, and wetland plants from a reservoir, Govind Ballabh (G.B.) Pant Sagar, in Singrauli Industrial region, India. The discharge point of a thermal power plant, a coal mine, and chlor-alkali effluent into the G.B. Pant Sagar were selected as sampling sites with one reference site in order to compare the findings. The concentrations of heavy metals in filtered water, sieved sediment samples (0.4-63 microm), and wetland plants were determined with particle-induced X-ray emission. The collected plants were Aponogeton natans, L. Engl. & Krause, Cyperus rotundus, L., Hydrilla verticillata, (L.f.) Royle, Ipomoea aquatica, Forssk., Marsilea quadrifolia, L., Potamogeton pectinatus, L., Eichhornia crassipes, (Mart.) Solms Monogr., Lemna minor, L., Spirodela polyrhiza (L.) Schleid. Linnaea, Azolla pinnata, R.Br., Vallisneria spiralis, L., and Polygonum amphibium, L. In general, metal concentration showed a significant positive correlation between industrial effluent, lake water, and lake sediment (p < 0.01). Likewise, significant positive correlation was recorded with metals concentration in plants and lake ambient, which further indicated the potential of aforesaid set of wetland macrophytes for pollution monitoring.     

Seasonal monitoring of heavy metals and physicochemical characteristics in a lentic ecosystem of subtropical industrial region, India

Assessment of seasonal changes in surface water quality is an important aspect for evaluating temporal variations of lentic ecosystem (lakes and reservoirs) pollution due to industrial effluent discharge. In this study, nine metals and 15 physicochemical parameters, collected from four sampling sites in a tropical lake receiving the discharge from thermal power plant, coal mine, and chloralkali industry, during the years from 2004 to 2005, were analyzed. For greater efficacy in monitoring of heavy metals, particle-induced X-ray emission has been used during present investigation. Different statistical techniques like analysis of variance, Pearson correlation, principal component analysis, and factor analysis were employed to evaluate the seasonal correlations of physicochemical parameters. Most of the metals and physicochemical parameters monitored in the present study exhibited high spatial and temporal variability. Pertaining to metal pollution, the most polluted site was Belwadah, i.e., waters and sediments had the highest concentration of all the relevant metals. The reference site was characterized by the presence of low concentrations of metals in waters and in sediments. Based on the high metal concentration recorded in lake ambient, drinking, bathing, and irrigation water should not be used by the local people at the effluent discharge points.     

Screening of brick-kiln area soil for determination of heavy metal Pb using LIBS

Rapid measurement of heavy metals in soil is an important factor in modeling the effect of industrial pollution on agricultural soil. Conventional methods of heavy metal analysis are relatively slow in terms of measurement/analysis time and sample preparation time with the requirement of skilled manpower. Our results highlight the quantitative analysis of toxic metal lead (Pb), for the first time, in an Indian agricultural soil, in the vicinity of brick-kiln area, Phaphamau, near Allahabad, India, by using a novel technique named as Laser-induced breakdown spectroscopy (LIBS). LIBS spectra of soil has been recorded in the wavelength range from ultraviolet (UV) to infrared region (200-1,100 nm). The suitability of Pb lines for drawing the calibration curve is checked and realized, for the first time, that 220.3 nm, which is observed in the UV region of LIBS spectra, is completely interference free and best suited for the quantification of trace amount of Pb in soil instead of any other Pb lines, because it has best linear regression coefficient and smallest standard deviation of the background signal. In the present work the detection limit for Pb in soil is found to be 45 ppm. Based on the present work the concentration of Pb in agricultural soil of brick-kiln area in Phaphamau is found to be congruent with 570 ppm, which is more than the regulatory standards imposed by US Environmental Protection Agency (400 ppm) for the presence of lead in soil, therefore, it is of great concern to us.     

Predicting dissolved oxygen concentration using kernel regression modeling approaches with nonlinear hydro-chemical data

Kernel function-based regression models were constructed and applied to a nonlinear hydro-chemical dataset pertaining to surface water for predicting the dissolved oxygen levels. Initial features were selected using nonlinear approach. Nonlinearity in the data was tested using BDS statistics, which revealed the data with nonlinear structure. Kernel ridge regression, kernel principal component regression, kernel partial least squares regression, and support vector regression models were developed using the Gaussian kernel function and their generalization and predictive abilities were compared in terms of several statistical parameters. Model parameters were optimized using the cross-validation procedure. The proposed kernel regression methods successfully captured the nonlinear features of the original data by transforming it to a high dimensional feature space using the kernel function. Performance of all the kernel-based modeling methods used here were comparable both in terms of predictive and generalization abilities. Values of the performance criteria parameters suggested for the adequacy of the constructed models to fit the nonlinear data and their good predictive capabilities.