Biodegradation of mono-chlorobenzene by using a trickle bed air biofilter (TBAB)

In the present study, performance of the trickle bed airbiofilter (TBAB) for treating mono-chlorobenzene (MCB) was evaluated for various influent volatile organic compound (VOC) loadings using coal and mixed consortium of activated sludge as the packing material. Microbial acclimation to MCB was achieved by exposing the system continuously for 31 d to an average inlet MCB concentration of 0.688 g m(-3) at an empty bed residence time (EBRT) of 188 s. The TBAB achieved maximum removal efficiency of 87% at an EBRT of 188 s for an inlet concentration of 0.681 g m(-3), which is quite significance than the values reported in the literature. Elimination capacities of MCB increased with an increase of the influent VOC loading, but an opposite trend was observed for the removal efficiency The maximum elimination capacity of the biofilter was 110.75 g m(-3) hr(-1) at an inlet MCB concentration of 1.47 g m(-3). The effect of starvation on the TBAB was also studied. After starvation, the TBAB lost its ability to degrade MCB initially However the biofilter recovered very quickly Evaluation of the concentration profile along the bed height indicated that the bottom section of TBAB has the best performance for all concentrations. By using Wani's method of macrokinetic determination based on simple Monod kinetics, the maximum removal rate of MCB, r(max) and saturation constant K(m) was to be found as 1.304 g m(-3)s(-1) and 113.446 g m(-3), respectively.     

Breast cancer incidence and exposure to pesticides among women originating from Jaipur

Environmental contamination by pesticides has been documented in biotic and abiotic components. These persistent organic pollutants are lipid soluble, nonbiodegradable, and endocrine disrupters. The present study was therefore planned to determine whether the levels of these pesticides like DDT and its metabolites DDD and DDE, dieldrin, heptachlor, and HCH and its isomers (alpha, beta, and gamma) were higher in blood of breast cancer patients when compared with normal women who did not suffer from major diseases like blood pressure, tuberculosis, diabetes, thyroid dysfunction, arthritis, cancer, etc. and had not undergone any major surgery. The results indicated that organochlorine pesticides taken for analysis were found significantly high in breast cancer patients irrespective of age, diet, and geographic distribution.     

Fluoride removal using capacitive deionization process employing carbon electrodes

Contamination of groundwater with fluoride poses adverse health impacts for humans. This study aims to investigate the feasibility of capacitive deionization process for fluoride removal from groundwater. In this study, composition of binder content was optimized and the experiments were performed using a lab scale batch reactor. Effect of initial ionic concentration on the removal efficiency was also studied. The electrodes were also evaluated for their efficiency to remove arsenic. The maximum fluoride removal efficiency obtained was 99.1% for the PVDF content of 15% (w/w) whereas for arsenic it was only 52%. The voltage applied across the electrodes was only 1.2V. Electrodes were tested for their physical strength and their characterization was done using Scanning Electron Microscope. Sorption kinetics of the electrodes was also investigated and was found that the adsorption followed elovich model most closely.     

Monitoring of organochlorine pesticides in and around Keoladeo National Park, Bharatpur, Rajasthan, India

Keoladeo National Park (KNP) is an important wintering ground for thousands of birds that undertake a perilous journey over the Himalaya to make a seasonal home in a wetland ecosystem. However, this wetland is now getting polluted by various types of contaminants such as pesticides because of the agricultural practices in the catchment area from where the park receives water. Keeping this in mind, the present study has been undertaken to assess the organochlorine pesticide (OCP) residues in the sediments inside and around KNP. Samples were collected from the different blocks of the park. The concentrations of α-HCH, β-HCH, γ-HCH, δ-HCH, S-HCH, aldrin, dieldrin, heptachlor, hept.epoxide, endosulfan-I, endosulfan-II, endo.sulfate, S-endosulfan, endrin, 4,4'-DDE, 4,4'-DDD, and DDT were quantified using gas chromatography with electron capture detection. Analysis showed that the samples were contaminated with the above mentioned pesticides and that the concentration of total OCPs in the sediments varied from 0.1173 (dieldrin) to 5.558 ppm (γ HCH) in the samples collected from inside the park, whereas a range of pesticides varying in concentration from 0.1245 (4,4'-DDD) to 7.54 ppm (γ HCH) was found in samples from outside the park. Residues of S-HCH and S-endosulfan were not detected in any of the sediment samples. The occurrence of pesticides inside the park is a major threat to the park's biodiversity. Eco-friendly agriculture practices with minimal use of inorganic chemicals are suggested to minimize the pesticide residue levels in the park.     

Monitoring of toxic elements present in sludge of industrial waste using CF-LIBS

Industrial waste is one of the main causes of environmental pollution. Laser-induced breakdown spectroscopy (LIBS) was applied to detect the toxic metals in the sludge of industrial waste water. Sludge on filter paper was obtained after filtering the collected waste water samples from different sections of a water treatment plant situated in an industrial area of Kanpur City. The LIBS spectra of the sludge samples were recorded in the spectral range of 200 to 500 nm by focusing the laser light on sludge. Calibration-free laser-induced breakdown spectroscopy (CF-LIBS) technique was used for the quantitative measurement of toxic elements such as Cr and Pb present in the sample. We also used the traditional calibration curve approach to quantify these elements. The results obtained from CF-LIBS are in good agreement with the results from the calibration curve approach. Thus, our results demonstrate that CF-LIBS is an appropriate technique for quantitative analysis where reference/standard samples are not available to make the calibration curve. The results of the present experiment are alarming to the people living nearby areas of industrial activities, as the concentrations of toxic elements are quite high compared to the admissible limits of these substances.     

Response Surface Method Coupled with First-Order Reliability Method Based Methodology for Groundwater Flow and Contaminant Transport Model for the Uranium Tailings Pond Site

Groundwater flow and contaminant transport modelling is carried out to predict the concentrations of radionuclides in groundwater beneath the tailings pond. This is used as a tool for radiological impact assessment studies. The geo-hydrological parameters involved in the modelling exhibit inherent uncertainty associated with their values. This uncertainty may get propagated to the model output, i.e. the dose to the public. The propagation of the uncertainty in the input parameters to the output is modelled using suitable methods of probabilistic analysis. Response surface method coupled with first-order reliability method is used to develop a methodology for estimating the probability that the dose rate value through drinking water pathway at a location around the tailings pond exceeds the WHO guidelines for drinking water, termed as the probability of exceedance of acceptable levels. This method also gives the estimate of sensitivity of the probability of exceedance to the different input parameters. It is observed that the probability of failure decreases as the distance from tailings pond centre is increased and beyond a distance of around 0.5 km from tailings pond centre, the probability reduces to zero. The work also brings out the importance of quantifying the uncertainty in case of actual field problems where there is wide variation in the values of the various parameters within the domain under study.     

Real-time bias-adjusted O3 and PM2.5 air quality index forecasts and their performance evaluations over the continental United States

The National Air Quality Forecast Capacity (NAQFC) system, which links NOAA’s North American Mesoscale (NAM) meteorological model with EPA’s Community Multiscale Air Quality (CMAQ) model, provided operational ozone (O₃) and experimental fine particular matter (PM_2.5) forecasts over the continental United States (CONUS) during 2008. This paper describes the implementation of a real-time Kalman Filter (KF) bias-adjustment technique to improve the accuracy of O₃ and PM_2.5 forecasts at discrete monitoring locations. The operational surface-level O₃ and PM_2.5 forecasts from the NAQFC system were post-processed by the KF bias-adjusted technique using near real-time hourly O₃ and PM_2.5 observations obtained from EPA’s AIRNow measurement network. The KF bias-adjusted forecasts were created daily, providing 24-h hourly bias-adjusted forecasts for O₃ and PM_2.5 at all AIRNow monitoring sites within the CONUS domain. The bias-adjustment post-processing implemented in this study requires minimal computational cost; requiring less than 10 min of CPU on a single processor Linux machine to generate 24-h hourly bias-adjusted forecasts over the entire CONUS domain.The results show that the real-time KF bias-adjusted forecasts for both O₃ and PM_2.5 have performed as well as or even better than the previous studies when the same technique was applied to the historical O₃ and PM_2.5 time series from archived AQF in earlier years. Compared to the raw forecasts, the KF forecasts displayed significant improvement in the daily maximum 8-h O₃ and daily mean PM_2.5 forecasts in terms of both discrete (i.e., reduced errors, increased correlation coefficients, and index of agreement) and categorical (increased hit rate and decreased false alarm ratio) evaluation metrics at almost all locations during the study period in 2008.     

High reduction of ozone and particulate matter during the 2016 G-20 summit in Hangzhou by forced emission controls of industry and traffic

Many regions in China experience air pollution episodes because of the rapid urbanization and industrialization over the past decades. Here we analyzed the effect of emission controls implemented during the G-20 2016 Hangzhou summit on air quality. Emission controls included a forced closure of highly polluting industries, and limiting traffic and construction emissions in the cities and surroundings. Particles with aerodynamic diameter lower than 2.5 μm (PM_2.5) and ozone (O₃) were measured. We also simulated air quality using a forecast system consisting of the two-way coupled Weather Research and Forecast and Community Multi-scale Air Quality (WRF-CMAQ) model. Results show PM_2.5 and ozone levels in Hangzhou during the G-20 Summit were considerably lower than previous to the G-20 Summit. The predicted concentrations of ozone were reduced by 25.4%, whereas the predicted concentrations of PM_2.5 were reduced by 56%.