Source apportionment of arsenic in atmospheric dust fall out in an urban residential area, Raipur, Central India

The components and quantities of atmospheric dust fallout have been reported to be the pollution indicator of large urban areas. The multiplicity and complexity of sources of atmospheric dusts in urban regions has put forward the need of source apportionment of these sources indicating their contribution to specific environmental receptor. The study presented here is focused on investigation of source contribution estimates of Arsenic in urban dust fallout in an urban-industrial area, Raipur, India. Source-receptor based representative sampling plan using longitudinal study design has been adopted. Six sampling sites have been identified on the basis of land use for development plan of anthropogenic activities and factors related to the transportation and dispersion pattern of atmospheric dusts. Source apportionment has been done using Chemical Mass Balance (CMB 8). Good fit parameters and relative source contribution has been analyzed and documented. Dominance of coal fired industries sources on arsenic levels measured at selected ambient residential receptors compared to line sources has been observed. Road-traffic has shown highest contribution of dust at indoor houses and out door-street automobile exhaust has shows highest contribution for arsenic. The results of CMB output and regression data of source-receptor dust matrices have shown comparable pattern

Variations in mass of the PM 10,PM 2.5 and PM 1 during the monsoon and the winter at New Delhi

PM10, PM2.5 and PM1 mass concentrations have been measured at Delhi (28°35'N; 77°12'E) during the August to December 2007. The running mean of PM10, PM2.5 and PM1 data shows large variations. The PM10, PM2.5 and PM1 were ranged from 20 to 180 μg/m3 during the monsoon and from 100 to 500 μg/m3 during the winter (up to 1200 μg/m3 in November due to Deepavali fireworks). For the same running mean cycles, higher mass concentrations in the PM10, PM2.5 and PM1 were corresponded with peaks in the relative humidity and lower levels linked to peaks in the ambient temperature. The evolutions of PM10, PM2.5 and PM1 concentrations after the elapsed times are simulated with mean mass scavenging coefficients. These evolution patterns clearly show the difference in washout of PM10 with impaction scavenging relative to those for PM2.5 and PM1 particles over different rainfall durations. Air-mass pathways traced with HYSPLIT model over the study area illustrates the nature of PM10, PM2.5 and PM1 levels with monsoon and winter air-mass circulations over Delhi

Visibility degradation during foggy period due to anthropogenic urban aerosol at Delhi, India

Fog which is defined as an obscurity near the surface layer of the atmosphere and is caused by a suspension of water droplets associated with visibility and its frequencies dominate in urban areas other than rural areas. It may occur due to increased air pollutant concentrations emanating from variety of sources in the urban areas. The increased pollution levels may lead to the atmospheric reactions resulting into the formation of secondary pollutants that may also lead to the needed cloud condensation nuclei. Northern part of India experience severe fog conditions (warm fog) during the winter period (November-January) every year. In this study, we have simultaneously measured the particulate mass concentration (0.23 mum to 20 mum in 16 size channels), meteorological parameters and atmospheric visibility in mega city Delhi during winter months of the years 2007-2008 in order to have an improved understanding of their role in fog formation. The effects of aerosols on fog formation are discussed through an analysis of trends in fog frequency and comparison with meteorological parameters especially visibility which is an indicator of aerosol loading in the lower atmosphere. The existing dataset is used to find linear regression amongst various parameters with due consideration of significance value. This satisfies the precondition for using these relations even in limited data set. The association between the meteorological parameter (visibility, depression temperature) and air pollutants are examined. The Windows software SPSS (version 17.0) is used to fit a linear regression model. The model explained the variation in visibility due to depression temperature and aerosols loading

Assessments of PM1, PM2.5 and PM10 concentrations in Delhi at different mean cycles

ABSTRACT Daily, monthly, seasonal and annual moving means of PM1, PM2.5 and PM10 concentrations from August, 2007 to October, 2008 at Delhi (28� 35' N; 77� 12' E), the seventh populous megacity in the world are presented. PM1, PM2.5 and PM10 concentrations varied seasonally with atmospheric processes and the anthropogenic activities. PM10 decreases during monsoon by ~25-80 �g m-3 and PM1 and PM2.5 by ~10-15 �g m-3 from their pre-monsoon levels. Emissions from fireworks during Deepawali in the post-monsoon season increases PM1, PM2.5 and PM10 levels by 300, 350 and 400 �g m-3, respectively over their monsoon levels. Seasonal variation of mixing heights, temperatures, winds and rainfall, accounts for the inter-annual variability of PM1, PM2.5, and PM10. Accordingly, wintertime PM1, PM2.5 and PM10 components contribute by ~30-33% to annual levels. PM10 in summer is higher by 8% to that of PM2.5 and by 9% to that of PM1. PM10 components in post-monsoon are lower by 5% to that of PM2.5 and by 7% to that of PM1. Also, PM1, PM2.5 and PM10 levels were higher during October, 2008 than those in 2007, but their levels were almost remain the same in August and September of 2007 and 2008. Moving means of PM1, PM2.5 and PM10 and their concentrations in different seasons are useful in policy making decisions thereupon aiming to improve the air quality in Delhi

PM2.5 chemical source profiles of emissions resulting from industrial and domestic burning activities in India

A study has been performed to develop PM2.5 (particles with aerodynamic diameters ≤ 2.5) chemically speciated source profiles of different industrial and domestic burning practices in India. A total of fifty-five PM2.5 samples have been collected in emissions resulting from (1) industrial furnaces, (2) household fuels, (3) municipal solid waste burning, and (4) welding workshop burning practices, and categorized for eleven subtypes of sources. The collected samples were subjected to chemical analysis for twenty-one elemental (Al, As, Ca, Cd, Co, Cr, Cu, Fe, Hg, K, Mg, Mn, Mo, Na, Ni, Pb, S, Sb, Se, V, Zn), nine ionic (Na+, K+, Mg2+, Ca2+, NH4+, Cl–, F–, NO3–, SO42–), OC, and EC source indicator species using atomic absorption spectrometry, ion chromatography and carbon analysis (thermal/optical transmittance method), respectively. The carbonaceous fraction was most abundant in household fuel burning emissions (47.6 ± 7.45% to 65.92 ± 13.13%). The ionic/elemental ratios of major inorganic constituents (Ca2+/Ca, Mg2+/Mg and Na+/Na) have been identified to describe the PM2.5 emissions from combustion or re-suspension dusts during industrial activities. Brick Kiln processes (BKP) have been identified as the major emitter of the highest number of toxic species (Cd, Co, Mo, Sb and V), followed by steel re-rolling mills (Hg and Pb) and steel processing industries (As, Ni). The source marker calculations also confirmed that K+, Mn, and As are good markers for biomass burning, metallurgical industrial emission, and coal burning, respectively, similar to the findings in previous studies

Chemical characterization of atmospheric particulate matter in Delhi, India, part II: Source apportionment studies using PMF 3.0

World Bank reports Delhi as a second most polluted megacity in the world for particulates pollution. In Delhi, PM10 (d ≤ 10 μm) aerosol samples were monitored throughout 2008 and their characterization for major chemical elements (Na, Mg, Al, Si, P, S, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, As, Br, Sr, Ba, Pb, Cd, Sn and Sb) and ions (Cl-, NO3-, SO42-, Na+, NH4+, K+, Mg2+ and Ca2+) have been documented in an earlier study. To resolve complexity in source apportionment for chemical constituents in PM10, UNMIX 6.0 and Positive Matrix Factorization (PMF 3.0) models are applied. Four factors were derived to explain routine sources of PM10 (crustal origin, road-traffic and secondary aerosols). Factor-1, designated as road-traffic source, has been determined by temporal correlation among Pb, Cu, Zn, Ni and V with strong correlation between Pb and Zn. This source factor-1 has shown more than 60% contribution to receptor site. Factor-2, referred as crustal origin due to strong inter-relationship among Si, Fe, Al, Ca and Mg, has also shown to be significant contribution to similar species in receptor matrix. Factor-3 ( NH4+, NO3-) has been differentiated due to contribution of secondary aerosols in the receptor region. This factor-3 has indicated major fraction of these ionic species for their uniform percentage variability, where mean values have been projected close to 75th percentile. Surprisingly, source factor-4 has explained the specific chloride source in the region with major contribution of 86%. For policymakers, results presented would serve as benchmark of source apportionments in Delhi

Characterisation of atmospheric aerosol by SEM-EDX and Ion-chromatography techniques for eastern Indo-Gangetic plain location, Varanasi, India

Atmospheric aerosol consists of both natural and anthropogenic origin. Studies have shown that continuous exposure to these particles is associated with a high percentage of death from respiratory and cardiovascular disease. In the present study, we have first time used both SEM-EDX analysis as well as chemical analysis to understand the differences in morphology and elemental composition of aerosols sample from a suburban clean and green area of Banaras Hindu University campus and some much polluted urban areas of the Varanasi city situated in the eastern Indo-Gangetic plain. The analysis was done by using scanning electron microscope (SEM) coupled with energy dispersive X-ray microanalyzer (EDX) and ionchromatography (IC). Analyses show that C, Ca, Na, S, Si, Al have dominated the sample

The plant-based immunomodulator curcumin as a potential candidate for the development of an adjunctive therapy for cerebral malaria

The clinical manifestations of cerebral malaria (CM) are well correlated with underlying major pathophysiological events occurring during an acute malaria infection, the most important of which, is the adherence of parasitized erythrocytes to endothelial cells ultimately leading to sequestration and obstruction of brain capillaries. The consequent reduction in blood flow, leads to cerebral hypoxia, localized inflammation and release of neurotoxic molecules and inflammatory cytokines by the endothelium. The pharmacological regulation of these immunopathological processes by immunomodulatory molecules may potentially benefit the management of this severe complication. Adjunctive therapy of CM patients with an appropriate immunomodulatory compound possessing even moderate anti-malarial activity with the capacity to down regulate excess production of proinflammatory cytokines and expression of adhesion molecules, could potentially reverse cytoadherence, improve survival and prevent neurological sequelae. Current major drug discovery programmes are mainly focused on novel parasite targets and mechanisms of action. However, the discovery of compounds targeting the host remains a largely unexplored but attractive area of drug discovery research for the treatment of CM. This review discusses the properties of the plant immune-modifier curcumin and its potential as an adjunctive therapy for the management of this complication

A Conserved Role for Syndecan Family Members in the Regulation of Whole-Body Energy Metabolism

Syndecans are a family of type-I transmembrane proteins that are involved in cell-matrix adhesion, migration, neuronal development, and inflammation. Previous quantitative genetic studies pinpointed Drosophila Syndecan (dSdc) as a positional candidate gene affecting variation in fat storage between two Drosophila melanogaster strains. Here, we first used quantitative complementation tests with dSdc mutants to confirm that natural variation in this gene affects variability in Drosophila fat storage. Next, we examined the effects of a viable dSdc mutant on Drosophila whole-body energy metabolism and associated traits. We observed that young flies homozygous for the dSdc mutation had reduced fat storage and slept longer than homozygous wild-type flies. They also displayed significantly reduced metabolic rate, lower expression of spargel (the Drosophila homologue of PGC-1), and reduced mitochondrial respiration. Compared to control flies, dSdc mutants had lower expression of brain insulin-like peptides, were less fecund, more sensitive to starvation, and had reduced life span. Finally, we tested for association between single nucleotide polymorphisms (SNPs) in the human SDC4 gene and variation in body composition, metabolism, glucose homeostasis, and sleep traits in a cohort of healthy early pubertal children. We found that SNP rs4599 was significantly associated with resting energy expenditure (P = 0.001 after Bonferroni correction) and nominally associated with fasting glucose levels (P = 0.01) and sleep duration (P = 0.044). On average, children homozygous for the minor allele had lower levels of glucose, higher resting energy expenditure, and slept shorter than children homozygous for the common allele. We also observed that SNP rs1981429 was nominally associated with lean tissue mass (P = 0.035) and intra-abdominal fat (P = 0.049), and SNP rs2267871 with insulin sensitivity (P = 0.037). Collectively, our results in Drosophila and humans argue that syndecan family members play a key role in the regulation of body metabolism