Size distribution and source identification of total suspended particulate matter and associated heavy metals in the urban atmosphere of Delhi

A study of the atmospheric particulate size distribution of total suspended particulate matter (TSPM) and associated heavy metal concentrations has been carried out for the city of Delhi. Urban particles were collected using a five-stage impactor at six sites in three different seasons, viz. winter, summer and monsoon in the year 2001. Five samples from each site in each season were collected. Each sample (filter paper) was extracted with a mixture of nitric acid, hydrochloric acid and hydrofluoric acid. The acid solutions of the samples were analysed in five-particle fractions by atomic absorption spectrometry (AAS). The impactor stage fractionation of particles shows that a major portion of TSPM concentration is in the form of PM0.7 (i.e. <0.7microm). Similarly, the most of the metal mass viz. Mn, Cr, Cd, Pb, Ni, and Fe are also concentrated in the PM0.7 mode. The only exceptions are size distributions pertaining to Cu and Ca. Though, Cu is more in PM0.7 mode, its presence in size intervals 5.4-1.6microm and 1.6-0.7microm is also significant, whilst in case of Ca there is no definite pattern in its distribution with size of particles. The average PM10.9 (i.e. <10.9microm) concentrations are approximately 90.2%+/-4.5%, 81.4%+/-1.4% and 86.4%+/-9.6% of TSPM for winter, summer and monsoon seasons, respectively. Source apportionment reveals that there are two sources of TSPM and PM10.9, while three and four sources were observed for PM1.6 (i.e. <1.6microm) and PM0.7, respectively. Results of regression analyses show definite correlations between PM10.9 and other fine size fractions, suggesting PM10.9 may adequately act as a surrogate for both PM1.6 and PM0.7, while PM1.6 may adequately act as a surrogate for PM0.7.     

Estimating nutrient loadings using chemical mass balance approach

The river Hindon is one of the important tributaries of river Yamuna in western Uttar Pradesh (India) and carries pollution loads from various municipal and industrial units and surrounding agricultural areas. The main sources of pollution in the river include municipal wastes from Saharanpur, Muzaffarnagar and Ghaziabad urban areas and industrial effluents of sugar, pulp and paper, distilleries and other miscellaneous industries through tributaries as well as direct inputs. In this paper, chemical mass balance approach has been used to assess the contribution from non-point sources of pollution to the river. The river system has been divided into three stretches depending on the land use pattern. The contribution of point sources in the upper and lower stretches are 95 and 81% respectively of the total flow of the river while there is no point source input in the middle stretch. Mass balance calculations indicate that contribution of nitrate and phosphate from non-point sources amounts to 15.5 and 6.9% in the upper stretch and 13.1 and 16.6% in the lower stretch respectively. Observed differences in the load along the river may be attributed to uncharacterized sources of pollution due to agricultural activities, remobilization from or entrainment of contaminated bottom sediments, ground water contribution or a combination of these sources.     

Associations between concentrations of selected perfluoroalkyl acids and concentrations of blood cadmium,lead, and total mercury

Environmental Science and Pollution Research - Data (N = 2552) from National Health and Nutrition Examination Survey for US adults aged ≥ 20 years for 2011–2016 were analyzed to...     

Protective role of zeolite on short- and long-term lead toxicity in the teleost fish Heteropneustes fossilis.

The high ion-exchange capacity of zeolite (sodium aluminium silicate) enhances the removal of lead from water, thus decreasing its availability to fish. Zeolites are very important in the field of environmental preservation due to the low cost and ecological compatibility. Zeolites can adsorb metallic ions by cation exchange reactions. Continuous exposure of the teleost fish Heteropneustes fossilis to sublethal concentrations of lead nitrate in water solution for short (35 days) and long (120 days) periods decreased both the soluble protein, RNA and glycogen contents in the liver and the body weight, but increased the cholesterol content. The presence of zeolite in the exposure solution decreased all of the adverse effects. In fish exposed to zeolite as feed additive, all the parameters improved in comparison to control fish, indicating that zeolites can be used safely in biological systems.     

Health impact assessment of auto rickshaw and cab drivers due to exposure to vehicular pollution in Delhi: an integrated approach

Environmental Science and Pollution Research - Vehicular emission is an important contributor to air pollution in the urban environment and impacts the health of commuters as well as drivers. The...     

Higher Cd adsorption on biogenic elemental selenium nanoparticles

Cadmium (Cd) is a carcinogenic metal contaminating the environment and ending up in wastewaters. There is therefore a need for improved methods to remove Cd by adsorption. Biogenic elemental selenium nanoparticles have been shown to adsorb Zn, Cu and Hg, but these nanoparticles have not been tested for Cd removal. Here we studied the time-dependency and adsorption isotherm of Cd onto biogenic elemental selenium nanoparticles using batch adsorption experiments. We measured ζ-potential values to assess the stability of nanoparticles loaded with Cd. Results show that the maximum Cd adsorption capacity amounts to 176.8 mg of Cd adsorbed per g of biogenic elemental selenium nanoparticles. The ζ-potential of Cd-loaded nanoparticles became less negative from ?32.7 to ?11.7 mV when exposing nanoparticles to an initial Cd concentration of 92.7 mg L^?1. This is the first study that demonstrates the high Cd uptake capacity of biogenic elemental selenium nanoparticles, of 176.8 mg g^?1, when compared to that of traditional adsorbents such as carboxyl-functionalized activated carbon, of 13.5 mg g^?1. An additional benefit is the easy solid–liquid separation by gravity settling due to coagulation of Cd-loaded biogenic elemental selenium nanoparticles.     

Chronic study of arsenic trioxide-induced hepatotoxicity in relation to arsenic liver accumulation in rats

This study measured activities of serum enzymes alkaline phosphatase, acid phosphatase, glutamic oxaloacetic transaminase (SGOT), and glutamic pyruvic transaminase (SGPT), markers of liver function in albino rats after continuous ingestion of arsenic trioxide (As₂0₃). For the study, treated animals were given AS₂O₃ (0.2 mg/100 g/day) orally for 180 days. After the completion of treatment, the blood was collected for the estimation of serum biochemical markers. The results obtained were compared with control group. Data showed a significant increase in SGOT and SGPT activity after 60 days of As₂0₃ administration. The level of alkaline phosphatase and acid phosphatase increased significantly after 90 and 120 days, respectively. Since the elevation of these serum enzymes is an indicator of hepatic damage, data indicate that As₂O₃ produces hepatotoxicity. When taken continuously, arsenic was also deposited in liver and blood and affected the enzymatic pathways. Total accumulated arsenic was determined by HG-AAS at 193.7 nm.     

Artificial neural network modeling of the river water quality—A case study

The paper describes the training, validation and application of artificial neural network (ANN) models for computing the dissolved oxygen (DO) and biochemical oxygen demand (BOD) levels in the Gomti river (India). Two ANN models were identified, validated and tested for the computation of DO and BOD concentrations in the Gomti river water. Both the models employed eleven input water quality variables measured in river water over a period of 10 years each month at eight different sites. The performance of the ANN models was assessed through the coefficient of determination (R²) (square of the correlation coefficient), root mean square error (RMSE) and bias computed from the measured and model computed values of the dependent variables. Goodness of the model fit to the data was also evaluated through the relationship between the residuals and model computed values of DO and BOD. The model computed values of DO and BOD by both the ANN models were in close agreement with their respective measured values in the river water. Relative importance and contribution of the input variables to the model output was evaluated through the partitioning approach. The identified ANN models can be used as tools for the computation of water quality parameters.