Organic matter determination for street dust in Delhi

The organic matter of street dust is considered as one of the causes for high human mortality rate. To understand the association, the street dust samples were collected from four different localities (industrial, residential, residential–commercial, and commercial) situated in the greater Delhi area of India. The loss-on-ignition method was used to determine the organic matter (OM) content in street dust. The OM content, potassium, calcium, sulfate, and nitrate concentrations of street dust in Delhi, India is measured to understand the spatial variation. Correlation analysis, analysis of variance, and factor analysis were performed to define the sources. The dust OM level ranges from 2.63 to 10.22 %. It is found through correlation and factor analysis that OM is primarily contributed from secondary aerosol and vehicular exhaust. The OM levels suggest that the use of a residential–commercial site for commercial purposes is polluting the street dust and creating the environmental and human health problems.     

High genotoxicity of shipyard contaminants on Allium cepa and calf thymus DNA

Water pollution is a major environmental problem worldwide. In particular, shipyards are contaminating waters with iron, lead and copper filings, paints, petrochemical products and solvents. There are only a few reports on the genotoxicity of shipyard contaminants. Here, we study genotoxic effects of surface water from five sites of Hooghly River in West Bengal, India, along the banks of which many shipbuilding and scrap industries are located. Genotoxicity was measured by the detection of micronuclei in Allium cepa and other chromosomal aberrations, as well as damage to genomic DNA of calf thymus. Results show that A. cepa roots treated with contaminated water induced morphological distortions, formation of micronuclei and various types of chromosomal aberrations. The mitotic index was lower than 50 % in the treated samples. The breakage of calf thymus DNA was time-dependent with acute damage of 100 % for overnight incubation as evidenced by agarose gel electrophoresis. We conclude that the workers of local shipbuilding and scrap industries, the residents of nearby areas and the aquatic biodiversity are vulnerable to contaminated waters.     

Indoor air quality modeling for PM10, PM2.5, and PM1.0 in naturally ventilated classrooms of an urban Indian school building

Assessment of indoor air quality (IAQ) in classrooms of school buildings is of prime concern due to its potential effects on student??s health and performance as they spend a substantial amount of their time (6?C7 h per day) in schools. A number of airborne contaminants may be present in urban school environment. However, respirable suspended particulate matter (RSPM) is of great significance as they may significantly affect occupants?? health. The objectives of the present study are twofold, one, to measure the concentrations of PM₁₀ (<10  $\upmu $ m), PM_2.5 (<2.5  $\upmu $ m), and PM_1.0 (<1.0  $\upmu $ m) in naturally ventilated classrooms of a school building located near a heavy-traffic roadway (9,755 and 4,296 vehicles/hour during weekdays and weekends, respectively); and second, to develop single compartment mass balance-based IAQ models for PM₁₀ (NVIAQM_pm10), PM_2.5 (NVIAQM_pm2.5), and PM_1.0 (NVIAQM_pm1.0) for predicting their indoor concentrations. Outdoor RSPM levels and classroom characteristics, such as size, occupancy level, temperature, relative humidity, and CO₂ concentrations have also been monitored during school hours. Predicted indoor PM₁₀ concentrations show poor correlations with observed indoor PM₁₀ concentrations (R ² = 0.028 for weekdays, and 0.47 for weekends). However, a fair degree of agreement (d) has been found between observed and predicted concentrations, i.e., 0.42 for weekdays and 0.59 for weekends. Furthermore, NVIAQM_pm2.5 and NVIAQM_pm1.0 results show good correlations with observed concentrations of PM_2.5 (R ² = 0.87 for weekdays and 0.9 for weekends) and PM_1.0 (R ² = 0.86 for weekdays and 0.87 for weekends). NVIAQM_pm10 shows the tendency to underpredict indoor PM₁₀ concentrations during weekdays as it does not take into account the occupant??s activities and its effects on the indoor concentrations during the class hours. Intense occupant??s activities cause resuspension or delayed deposition of PM₁₀. The model results further suggests conductance of experimental and physical simulation studies on dispersion of particulates indoors to investigate their resuspension and settling behavior due to occupant??s activities/movements. The models have been validated at three different classroom locations of the school site. Sensitivity analysis of the models has been performed by varying the values of mixing factor (k) and newly introduced parameter R _c. The results indicate that the change in values of k (0.33 to 1.00) does not significantly affect the model performance. However, change in value of R _c (0.001 to 0.500) significantly affects the model performance.