Application of drastic model and GIS: for assessing vulnerability in hard rock granitic aquifer

Geographic information system (GIS) has become one of the leading tools in the field of hydrogeological science that helps in assessing, monitoring, and conserving groundwater resources. Groundwater is a finite resource, which is being overexploited due to increase in demand over the years leading to decrease in its potentiality. In the present study, DRASTIC model has been used to prepare groundwater vulnerable zone in hard rock aquifer of granitic terrain. The main objective is to determine susceptible zone for groundwater pollution by integrating hydrogeological layers in GIS environment. The layers such as depth of aquifer, recharge, aquifer yield, soil type, topography, vadose zone, and transmissivity are incorporated in the DRASTIC model. The final output of the map shows that around 60% of the area falls under low to no risk of pollution zone. The high risk of pollution zones are mostly present towards the margin of southeastern periphery. The lower part of the basin as well as small area on northern side falls under moderate risk of pollution zone. For the assessment of groundwater pollution zone, 24 groundwater samples have been collected from different vulnerable zones. The chemical analysis of sample shows that the southeastern margin of basin has relatively high concentration of nitrate as compared to other parts of the basin. It is present in high pollution zone as well as moderate pollution zone. The present model can be used for assessment and management of groundwater.     

Emissions Variability Processor (EMVAP): Design,evaluation, and application

Emissions of pollutants such as SO₂ and NOx from external combustion sources can vary widely depending on fuel sulfur content, load, and transient conditions such as startup, shutdown, and maintenance/malfunction. While monitoring will automatically reflect variability from both emissions and meteorological influences, dispersion modeling has been typically conducted with a single constant peak emission rate. To respond to the need to account for emissions variability in addressing probabilistic 1-hr ambient air quality standards for SO₂ and NO₂, we have developed a statistical technique, the Emissions Variability Processor (EMVAP), which can account for emissions variability in dispersion modeling through Monte Carlo sampling from a specified frequency distribution of emission rates. Based upon initial AERMOD modeling of from 1 to 5 years of actual meteorological conditions, EMVAP is used as a postprocessor to AERMOD to simulate hundreds or even thousands of years of concentration predictions. This procedure uses emissions varied hourly with a Monte Carlo sampling process that is based upon the user-specified emissions distribution, from which a probabilistic estimate can be obtained of the controlling concentration. EMVAP can also accommodate an advanced Tier 2 NO₂ modeling technique that uses a varying ambient ratio method approach to determine the fraction of total oxides of nitrogen that are in the form of nitrogen dioxide. For the case of the 1-hr National Ambient Air Quality Standards (NAAQS, established for SO₂ and NO₂), a “critical value” can be defined as the highest hourly emission rate that would be simulated to satisfy the standard using air dispersion models assuming constant emissions throughout the simulation. The critical value can be used as the starting point for a procedure like EMVAP that evaluates the impact of emissions variability and uses this information to determine an appropriate value to use for a longer term (e.g., 30-day) average emission rate that would still provide protection for the NAAQS under consideration. This paper reports on the design of EMVAP and its evaluation on several field databases that demonstrate that EMVAP produces a suitably modest overestimation of design concentrations. We also provide an example of an EMVAP application that involves a case in which a new emission limitation needs to be considered for a hypothetical emission unit that has infrequent higher-than-normal SO₂ emissions.

ImplicationsEmissions of pollutants from combustion sources can vary widely depending on fuel sulfur content, load, and transient conditions such as startup and shutdown. While monitoring will automatically reflect this variability on measured concentrations, dispersion modeling is typically conducted with a single peak emission rate assumed to occur continuously. To realistically account for emissions variability in addressing probabilistic 1-hr ambient air quality standards for SO₂ and NO₂, the authors have developed a statistical technique, the Emissions Variability Processor (EMVAP), which can account for emissions variability in dispersion modeling through Monte Carlo sampling from a specified frequency distribution of emission rates.     

Dissipation kinetics of spiromesifen on tea (Camellia sinensis) under tropical conditions

Spiromesifen (Oberon) is a new insecticide and miticide of chemical class ketoenol active against white flies (Bemisia spp., Trialeuroides spp.) and spider mites (Tetranychus and Panonychus spp.). Due to its potential significance in insect resistance management, it is important to establish its behaviour on crop and environment. In the present study, the degradation/dissipation of spiromesifen on tea crop under tropical environmental conditions was studied and its DT(50) (t(1/2)), and DT(90) (time to reduce to 90% of the initial value) were estimated. Spiromesifen was sprayed on tea crop after first rain flush at four different locations @ 96 and 192ga.i.ha(-1). Samples of tea leaves were drawn at 0, 1, 3, 5, 7, 10, 15, 21 and 30 days after treatment and that of soil at 10 days after treatment and at harvest from 0 to 15 and 15 to 30cm layers. After crude extraction of tea leaves for spiromesifen residues with acetone:water, the contents were partitioned with cyclohexane:ethyl acetate and cleaned up on Florosil column. Soil residues were also extracted similarly. Quantification of residues was done on GC-MS in Selected Ion Monitoring (SIM) mode in mass range 271-274m/z. The LOQ of this method was found to be 0.05microgg(-1) while LOD being 0.015microgg(-1). The DT(50) of spiromesifen when applied at recommended doses in tea leaves was found to be 5.0-8.5 days. Ninety-nine percent degradation was found to occur within 33-57 days after application. In soil, no residues of spiromesifen were detectable 10 days after treatment.     

Removal of Pb(II) ions from aqueous solution and industrial effluent using natural biosorbents

Purpose

The purpose of the research is to investigate the applicability of the low-cost natural biosorbents for the removal of Pb(II) ions from aqueous solution and effluent from battery industry.

Methods

Six different biosorbents namely rice straw, rice bran, rice husk, coconut shell, neem leaves, and hyacinth roots have been used for the removal of Pb(II) ions from aqueous solution in batch process. All the biosorbents were collected from local area near Kolkata, West Bengal, India. The removal efficiency was determined in batch experiments for each biosorbent.

Results

The biosorbents were characterized by SEM, FTIR, surface area, and point of zero charge. The sorption kinetic data was best described by pseudo-second-order model for all the biosorbents except rice husk which followed intraparticle diffusion model. Pb(II) ions adsorption process for rice straw, rice bran, and hyacinth roots were governed predominately by film diffusion, but in the case of rice husk, it was intraparticle diffusion. Film diffusion and intraparticle diffusion were equally responsible for the biosorption process onto coconut shell and neem leaves. The values of mass transfer coefficient indicated that the velocity of the adsorbate transport from the bulk to the solid phase was quite fast for all cases. Maximum monolayer sorption capacities onto the six natural sorbents studied were estimated from the Langmuir sorption model and compared with other natural sorbents used by other researchers. The Elovich model, the calculated values of effective diffusivity, and the sorption energy calculated by using the Dubinin?CRadushkevich isotherm were indicated that the sorption process was chemical in nature. The thermodynamic studies indicated that the adsorption processes were endothermic. FTIR studies were carried out to understand the type of functional groups responsible for Pb(II) ions binding process. Regeneration of biosorbents were carried out by desorption studies using HNO₃. Battery industry effluents were used for the application study to investigate applicability of the biosorbents.

Conclusion

The biosorbents can be utilized as low-cost sorbents for the removal of Pb(II) ions from wastewater.     

Breakthrough adsorption study of migratory nickel in fine-grained soil.

The present study was conducted to evaluate the breakthrough curve for nickel adsorption in fine-grained soil from a nearby ash pond site of a thermal power plant. Nickel was found to be the major polluting solute in the ash sluicing wastewater. The adsorption of nickel by vertical soil column batch test and horizontal migration test was carried out in the laboratory. Field investigation was conducted also, by installing test wells around the ash pond site. Experimental results showed a good adsorptive capacity of soil for nickel ions. The breakthrough curves showed a reasonable fitting with a one-dimensional mathematical model. The breakthrough curves yielded from field test results showed good agreement with a two-dimensional mathematical model.     

Revised algorithm for estimating light extinction from IMPROVE particle speciation data

The Interagency Monitoring of Protected Visual Environments (IMPROVE) particle monitoring network consists of approximately 160 sites at which fine particulate matter (PM2.5) mass and major species concentrations and course particulate matter (PM10) mass concentrations are determined by analysis of 24-hr duration sampling conducted on a 1-day-in-3 schedule A simple algorithm to estimate light extinction from the measured species concentrations was incorporated in the 1999 Regional Haze Rule as the basis for the haze metric used to track haze trends. A revised algorithm was developed that is more consistent with the recent atmospheric aerosol literature and reduces bias for high and low light extinction extremes. The revised algorithm differs from the original algorithm in having a term for estimating sea salt light scattering from Cl(-) ion data, using 1.8 instead of 1.4 for the mean ratio of organic mass to measured organic carbon, using site-specific Rayleigh scattering based on site elevation and mean temperature, employing a split component extinction efficiency associated with large and small size mode sulfate, nitrate and organic mass species, and adding a term for nitrogen dioxide (NO2) absorption for sites with NO2 concentration information. Light scattering estimates using the original and the revised algorithms are compared with nephelometer measurements at 21 IMPROVE monitoring sites. The revised algorithm reduces the underprediction of high haze periods and the overprediction of low haze periods compared with the performance of the original algorithm. This is most apparent at the hazier monitoring sites in the eastern United States. For each site, the PM10 composition for days selected as the best 20% and the worst 20% haze condition days are nearly identical regardless of whether the basis of selection was light scattering from the original or revised algorithms, or from nephelometer-measured light scattering.     

A Visual Basic simulation software tool for performance analysis of a membrane-based advanced water treatment plant

A Visual Basic simulation software (WATTPPA) has been developed to analyse the performance of an advanced wastewater treatment plant. This user-friendly and menu-driven software is based on the dynamic mathematical model for an industrial wastewater treatment scheme that integrates chemical, biological and membrane-based unit operations. The software-predicted results corroborate very well with the experimental findings as indicated in the overall correlation coefficient of the order of 0.99. The software permits pre-analysis and manipulation of input data, helps in optimization and exhibits performance of an integrated plant visually on a graphical platform. It allows quick performance analysis of the whole system as well as the individual units. The software first of its kind in its domain and in the well-known Microsoft Excel environment is likely to be very useful in successful design, optimization and operation of an advanced hybrid treatment plant for hazardous wastewater.