Preparation of black lyophilic ink using the carbon soot emitted by vehicles

Environmental Science and Pollution Research - The carbon soot is formed as a consequence of incomplete combustion of hydrocarbons and organic matter. It causes respiratory diseases like lung...     

Integrated approach for demarcating subsurface pollution and saline water intrusion zones in SIPCOT area: a case study from Cuddalore in Southern India

This paper deals with a systematic hydrogeological, geophysical, and hydrochemical investigations carried out in SIPCOT area in Southern India to demarcate groundwater pollution and saline intrusion through Uppanar River, which flows parallel to sea coast with high salinity (average TDS 28, 870 mg/l) due to back waters as well as discharge of industrial and domestic effluents. Hydrogeological and geophysical investigations comprising topographic survey, self-potential, multi-electrode resistivity imaging, and water quality monitoring were found the extent of saline water intrusion in the south and pockets of subsurface pollution in the north of the study area. Since the area is beset with highly permeable unconfined quaternary alluvium forming potential aquifer at shallow depth, long-term excessive pumping and influence of the River have led to lowering of the water table and degradation of water quality through increased salinity there by generating reversal of hydraulic gradient in the south. The improper management of industrial wastes and left over chemicals by closed industries has led surface and subsurface pollution in the north of the study area.     

Application and Evaluation of Two Air Quality Models for Particulate Matter for a Southeastern U.S. Episode

Abstract

The Models-3 Community Multiscale Air Quality (CMAQ) Modeling System and the Particulate Matter Comprehensive Air Quality Model with extensions (PMCAMx) were applied to simulate the period June 29–July 10, 1999, of the Southern Oxidants Study episode with two nested horizontal grid sizes: a coarse resolution of 32 km and a fine resolution of 8 km. The predicted spatial variations of ozone (O₃), particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM_2.5), and particulate matter with an aerodynamic diameter less than or equal to 10 μm (PM₁₀) by both models are similar in rural areas but differ from one another significantly over some urban/suburban areas in the eastern and southern United States, where PMCAMx tends to predict higher values of O₃ and PM than CMAQ. Both models tend to predict O₃ values that are higher than those observed. For observed O₃ values above 60 ppb, O₃ performance meets the U.S. Environmental Protection Agency's criteria for CMAQ with both grids and for PMCAMx with the fine grid only. It becomes unsatisfactory for PMCAMx and marginally satisfactory for CMAQ for observed O₃ values above 40 ppb.

Both models predict similar amounts of sulfate (SO₄ ^2?) and organic matter, and both predict SO₄ ^2? to be the largest contributor to PM_2.5. PMCAMx generally predicts higher amounts of ammonium (NH₄ ⁺), nitrate (NO₃ ^?), and black carbon (BC) than does CMAQ. PM performance for CMAQ is generally consistent with that of other PM models, whereas PMCAMx predicts higher concentrations of NO₃ ^?,NH₄ ⁺, and BC than observed, which degrades its performance. For PM₁₀ and PM_2.5 predictions over the southeastern U.S. domain, the ranges of mean normalized gross errors (MNGEs) and mean normalized bias are 37–43% and –33–4% for CMAQ and 50–59% and 7–30% for PMCAMx. Both models predict the largest MNGEs for NO₃ ^? (98–104% for CMAQ, 138–338% for PMCAMx). The inaccurate NO₃ ^? predictions by both models may be caused by the inaccuracies in the ammonia emission inventory and the uncertainties in the gas/particle partitioning under some conditions. In addition to these uncertainties, the significant PM overpredictions by PMCAMx may be attributed to the lack of wet removal for PM and a likely underprediction in the vertical mixing during the daytime.     

Rainfall trends in twentieth century over Kerala,India

Attempts were made to study temporal variation in monthly, seasonal and annual rainfall over Kerala, India, during the period from 1871 to 2005. Longterm changes in rainfall determined by Man-Kendall rank statistics and linear trend. The analysis revealed significant decrease in southwest monsoon rainfall while increase in post-monsoon season over the State of Kerala which is popularly known as the “Gateway of summer monsoon”. Rainfall during winter and summer seasons showed insignificant increasing trend. Rainfall during June and July showed significant decreasing trend while increasing trend in January, February and April. Hydel power generation and water availability during summer months are the concern in the State due to rainfall decline in June and July, which are the rainiest months. At the same time, majority of plantation crops are likely to benefit due to increase in rainfall during the post-monsoon season if they are stable and prolonged.     

Aerobic treatment of palm oil mill effluent

In this study treatment of palm oil mill effluent (POME) was investigated using aerobic oxidation based on an activated sludge process. The effects of sludge volume index, scum index and mixed liquor suspended solids during the acclimatizing phase and biomass build-up phase were investigated in order to ascertain the reactor stability. The efficiency of the activated sludge process was evaluated by treating anaerobically digested and diluted raw POME obtained from Golden Hope Plantations, Malaysia. The treatment of POME was carried out at a fixed biomass concentration of 3900+/-200mg/L, whereas the corresponding sludge volume index was found to be around 105+/-5mL/g. The initial studies on the efficiency of the activated sludge reactor were carried out using diluted raw POME for varying the hydraulic retention time, viz: 18, 24, 30 and 36h and influent COD concentration, viz: 1000, 2000, 3000, 4000 and 5000mg/L, respectively. The results showed that at the end of 36h of hydraulic retention time for the above said influent COD, the COD removal efficiencies were found to be 83%, 72%, 64%, 54% and 42% whereas at 24h hydraulic retention time they were 57%, 45%, 38%, 30% and 27%, respectively. The effectiveness of aerobic oxidation was also compared between anaerobically digested and diluted raw POME having corresponding CODs of 3908 and 3925mg/L, for varying hydraulic retention time, viz: 18, 24, 30, 36, 42, 48, 54 and 60h. The dissolved oxygen concentration and pH in the activated sludge reactor were found to be 1.8-2.2mg/L and 7-8.5, respectively. The scum index was found to rise from 0.5% to 1.9% during the acclimatizing phase and biomass build-up phase.     

Modeling Atmospheric Mercury Deposition in the Vicinity of Power Plants

Abstract

Two mathematical models of the atmospheric fate and transport of mercury (Hg), an Eulerian grid–based model and a Gaussian plume model, are used to calculate the atmospheric deposition of Hg in the vicinity (i.e., within 50 km) of five coal–fired power plants. The former is applied using two different horizontal resolutions: coarse (84 km) and fine (16.7 km). More than 96% of the power plant Hg emissions are calculated with the plume model to be transported beyond 50 km from the plants. The grid–based model predicts a lower fraction to be transported beyond 50 km: >91% with a coarse resolution and >95% with a fine resolution. The contribution of the power plant emissions to total Hg deposition within a radius of 50 km from the plants is calculated to be <8% with the plume model, <14% with the Eulerian model with a coarse resolution, and <10% with the Eulerian model with a fine resolution. The Eulerian grid–based model predicts greater local impacts than the plume model because of artificially enhanced vertical dispersion; the former predicts about twice as much Hg deposition as the latter when the area considered is commensurate with the resolution of the grid–based model. If one compares the local impacts for an area that is significantly less than the grid–based model resolution, then the grid–based model may predict lower local deposition than the plume model, because two compensating errors affect the results obtained with the grid–based model: initial dilution of the power plant emissions within one or more grid cells and enhanced vertical mixing to the ground.     

Partial characterization of the exopolysaccharide from Oscillatoria trichoides Szafer and the role of released polysaccharide in sequestration of Cr6+

The structural investigation and the chromium adsorptive potential of an exopolysaccharide (EPS) released during the growth of an indigenous cyanobacterium, Oscillatoria trichoides Szafer, were investigated in a laboratory‐scale study. The results showed that, of the total EPS produced, 410.53 milligrams/gram (mg g^?1) were released polysaccharides (RPS) and 11.36 mg g^?1 were capsular polysaccharides (CPS). The sorption of hexavalent chromium (Cr⁶⁺) by the RPS achieved a maximum amount of metal removal (q_max) value of 76.92 mg g^?1 of polysaccharide dry weight. The highest coefficient of determination (0.9742) for the Langmuir adsorption model indicates best fitness of the model in explaining the sorption as a unilayer process. Equilibrium studies indicated that 30 to 40 milligrams per liter initial chromium concentration and a pH of 2 were optimal for biosorption of chromium by the RPS. Scanning electron microscopy with energy‐dispersive X‐ray spectroscopy analysis of Cr⁶⁺‐treated RPS showed the presence of 3.76% bound chromium. Compositional analysis of the EPS showed the presence of carbohydrates, proteins, pyruvic acid, and hexosamines. High‐performance liquid chromatography analysis demonstrated the presence of hexoses, as neutral sugars and glucuronic acid as an acidic sugar. The presence of carboxylic groups was also detected by infrared spectroscopy. The presence of these chemical constituents may serve as binding sites for the metal ions; therefore, the RPS of this species appears to be a promising biosorbent for Cr⁶⁺.     

Application and evaluation of two air quality models for particulate matter for a southeastern U.S. episode

The Models-3 Community Multiscale Air Quality (CMAQ) Modeling System and the Particulate Matter Comprehensive Air Quality Model with extensions (PMCAMx) were applied to simulate the period June 29-July 10, 1999, of the Southern Oxidants Study episode with two nested horizontal grid sizes: a coarse resolution of 32 km and a fine resolution of 8 km. The predicted spatial variations of ozone (O3), particulate matter with an aerodynamic diameter less than or equal to 2.5 microm (PM2.5), and particulate matter with an aerodynamic diameter less than or equal to 10 microm (PM10) by both models are similar in rural areas but differ from one another significantly over some urban/suburban areas in the eastern and southern United States, where PMCAMx tends to predict higher values of O3 and PM than CMAQ. Both models tend to predict O3 values that are higher than those observed. For observed O3 values above 60 ppb, O3 performance meets the U.S. Environmental Protection Agency's criteria for CMAQ with both grids and for PMCAMx with the fine grid only. It becomes unsatisfactory for PMCAMx and marginally satisfactory for CMAQ for observed O3 values above 40 ppb. Both models predict similar amounts of sulfate (SO4(2-)) and organic matter, and both predict SO4(2-) to be the largest contributor to PM2.5. PMCAMx generally predicts higher amounts of ammonium (NH4+), nitrate (NO3-), and black carbon (BC) than does CMAQ. PM performance for CMAQ is generally consistent with that of other PM models, whereas PMCAMx predicts higher concentrations of NO3-, NH4+, and BC than observed, which degrades its performance. For PM10 and PM2.5 predictions over the southeastern U.S. domain, the ranges of mean normalized gross errors (MNGEs) and mean normalized bias are 37-43% and -33-4% for CMAQ and 50-59% and 7-30% for PMCAMx. Both models predict the largest MNGEs for NO3- (98-104% for CMAQ 138-338% for PMCAMx). The inaccurate NO3- predictions by both models may be caused by the inaccuracies in the ammonia emission inventory and the uncertainties in the gas/particle partitioning under some conditions. In addition to these uncertainties, the significant PM overpredictions by PMCAMx may be attributed to the lack of wet removal for PM and a likely underprediction in the vertical mixing during the daytime.     

The sensitivity of PM2.5 source-receptor relationships to atmospheric chemistry and transport in a three-dimensional air quality model

Air quality model simulations constitute an effective approach to developing source-receptor relationships (so-called transfer coefficients in the risk analysis framework) because a significant fraction of particulate matter (particularly PM2.5) is secondary (i.e., formed in the atmosphere) and, therefore, depends on the atmospheric chemistry of the airshed. In this study, we have used a comprehensive three-dimensional air quality model for PM2.5 (SAQM-AERO) to compare three approaches to generating episodic transfer coefficients for several source regions in the Los Angeles Basin. First, transfer coefficients were developed by conducting PM2.5 SAQM-AERO simulations with reduced emissions of one of four precursors (i.e., primary PM, sulfur dioxide (SO2), oxides of nitrogen (NOx), and volatile organic compounds) from each source region. Next, we calculated transfer coefficients using two other methods: (1) a simplified chemistry for PM2.5 formation, and (2) simplifying assumptions on transport using information limited to basin-wide emission reductions. Transfer coefficients obtained with the simplified chemistry were similar to those obtained with the comprehensive model for VOC emission changes but differed for NOx and SOz emission changes. The differences were due to the parameterization of the rates of secondary PM formation in the simplified chemistry. In 90% of the cases, transfer coefficients estimated using only basin-wide information were within a factor of two of those obtained with the explicit source-receptor simulations conducted with the comprehensive model. The best agreement was obtained for VOC emission changes; poor agreement was obtained for primary PM2.5.     

Assessment of deep aquifer groundwater quality in a geographically unique climatic region of Southern Western Ghats,India using water quality indices

Water quality index (WQI) models are generally used in hydrochemical studies to simplify complex data into single values to reflect the overall quality. In this study, deep groundwater quality in the Chittur and Palakkad Taluks of the Bharathapuzha river basin of Kerala, India, was assessed by employing the WQI method developed by the Canadian Council of Ministers of the Environment (CCME). The assessment of overall water quality is indispensable due to the specific characteristics of the study area, such as geography, climate, over-drafting, and prevalent agricultural practices. Forty representative samples were collected from the study area for monsoon (MON) and pre-monsoon (PRM) seasons. The results showed a general increase of contents from MON to PRM. The major cations were spread in the order Ca²⁺>Na+>Mg²⁺>K⁺ and the anions HCO₃⁻>Cl⁻>CO₃²⁻ based on their relative abundance. Among various parameters analysed, alkalinity and bicarbonate levels during MON were comparatively high, which is indicative of carbonate weathering, and 90% of the samples failed to meet the World Health Organization (WHO, 2017)/Bureau of Indian Standards (BIS, 2012) drinking water guidelines. The CCME WQI analysis revealed that nearly 50% of the samples during each season represented good and excellent categories. The samples in the poor category comprised 10% in MON and 15% in PRM. The overall WQI exhibited 15% of poor category samples as well. The spatial depiction of CCME WQI classes helped to expose zones of degraded quality in the centre to eastward parts. The spatial and temporal variations of CCME WQI classes and different physicochemical attributes indicated the influence of common factors attributing to the deep groundwater quality. The study also revealed inland salinity at Kolluparamba and Peruvamba stations, where agricultural activities were rampant with poor surface water irrigation.