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...     

Evaluation of accuracy of linear regression models in predicting urban stormwater discharge characteristics

Stormwater runoff has been identified as a source of pollution for the environment, especially for receiving waters. In order to quantify and manage the impacts of stormwater runoff on the environment, predictive models and mathematical models have been developed. Predictive tools such as regression models have been widely used to predict stormwater discharge characteristics. Storm event characteristics, such as antecedent dry days （ADD）, have been related to response variables, such as pollutant loads and concentrations. However it has been a controversial issue among many studies to consider ADD as an important variable in predicting stormwater discharge characteristics. In this study, we examined the accuracy of general linear regression models in predicting discharge characteristics of roadway runoff. A total of 17 storm events were monitored in two highway segments, located in Gwangju, Korea. Data from the monitoring were used to calibrate United States Environmental Protection Agency＇s Storm Water Management Model （SWMM）. The calibrated SWMM was simulated for 55 storm events, and the results of total suspended solid （TSS） discharge loads and event mean concentrations （EMC） were extracted. From these data, linear regression models were developed. R2 and p-values of the regression of ADD for both TSS loads and EMCs were investigated. Results showed that pollutant loads were better predicted than pollutant EMC in the multiple regression models. Regression may not provide the true effect of site-specific characteristics, due to uncertainty in the data.     

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.     

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.     

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.     

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.     

Nitrogen and sulphur mustard induced histopathological observations in mouse visceral organs

Nitrogen mustards (HN) and sulphur mustard (SM) are potent alkylating blister inducing chemical warfare agents. Single 1.0 LD50 dose produced a progressive fall in body weight from second day onwards in all groups of mustard agents exposed animals. Histological examination of spleen, liver skin and kidney revealed significant histopathological lesions in nitrogen mustards and sulphur mustard. These lesions include granulovascular degeneration with perinuclear clumping of the cytoplasm of hepatocytes and renal parenchymal cells. Renal lesions were characterized by congestion and hemorrhage. The maximum toxic manifestation were noted in spleen and skin of HN-3 exposed mice while sulphur mustard reported maximum toxicity in liver and kidneys. The study suggests both nitrogen mustards and sulphur mustard to be extremely toxic by percutaneous route based on histopathological observation and can contributed to earlier reported free radical generation by these toxicants.     

Impact of anthropogenic input on physicochemical parameters and trace metals in marine surface sediments of Bay of Bengal off Chennai, India

The study of heavy metal distribution in coastal surface sediments is an important component in understanding the exogenic cycling as well as in assessing the effect of anthropogenic influences on the marine ecosystem. In this study, surface sediment samples were collected from five different traverses along the innershelf of Bay of Bengal, off Chennai, India during pre- and post-monsoon seasons. The results of Spearmen correlation matrix, factor and cluster analysis, enrichment and contamination factor analysis, and geoaccumulation index of the heavy metals analyzed in the collected surface sediment were discussed. The level of both enrichment and contamination factor are shown in following order Cd > Cu > Cr > Ni > Pb > Co > Zn > Mn > Fe > Hg. The geoaccumulation index suggests that Cd and Cu are strongly to extremely pollute the sediments in both seasons. The results strongly indict anthropogenic sources for moderate input of Cd and Cu in to the innershelf of Chennai coast.     

Cascading ecological effects of low-level phosphorus enrichment in the Florida everglades

Few studies have examined long-term ecological effects of sustained low-level nutrient enhancement on wetland biota. To determine sustained effects of phosphorus (P) addition on Everglades marshes we added P at low levels (5, 15, and 30 microg L(-1) above ambient) for 5 yr to triplicate 100-m flow-through channels in pristine marsh. A cascade of ecological responses occurred in similar sequence among treatments. Although the rate of change increased with dosing level, treatments converged to similar enriched endpoints, characterized most notably by a doubling of plant biomass and elimination of native, calcareous periphyton mats. The full sequence of biological changes occurred without an increase in water total P concentration, which remained near ambient levels until Year 5. This study indicates that Everglades marshes have a near-zero assimilative capacity for P without a state change, that ecosystem responses to enrichment accumulate over time, and that downstream P transport mainly occurs through biota rather than the water column.