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The activity concentrations of soil samples collected from thirty different locations of Malwa region of Punjab were determined
by using HPGe detector based on high-resolution gamma spectrometry system. The range of activity concentrations of 226Ra, 232Th and 40K in the soil from the studied areas varies from 18.37 Bq kg−1 (Sangrur) to 53.11 Bq kg−1 (Sitoguno), 57.28 Bq kg−1 (Dhanola) to 148.28 Bq kg−1 (Sitoguno) and 211.13 Bq kg−1 (Sunam) to 413.27 Bq kg−1 (Virk Khera) with overall mean values of 35 Bq kg−1, 80 Bq kg−1and 317 Bq kg−1 respectively. The absorbed dose rate calculated from activity concentration of 226Ra, 232Th and 40K ranges between 8.47 and 24.48, 35.68 and 92.38, and 8.74 and 17.11 nGy h−1, respectively. The total absorbed dose in the study area ranges from 58.08 nGy h−1 to 130.85 nGy h−1 with an average value of 79.11 nGy h−1. The calculated values of external hazard index (Hex) for the soil samples of the study area range from 0.35 to 0.79. Since these values are lower than unity, therefore, according
to the Radiation Protection 112 (European Commission. Radiation Protection 112 1999) report, soil from these regions is safe and can be used as a construction material without posing any significant radiological
threat to population. 相似文献
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C. Hogrefe S. Roselle R. Mathur S.T. Rao S. Galmarini 《Journal of the Air & Waste Management Association (1995)》2014,64(4):388-405
This study presents an evaluation of summertime ozone concentrations over North America (NA) and Europe (EU) using the database generated from Phase 1 of the Air Quality Model Evaluation International Initiative (AQMEII). The analysis focuses on identifying temporal and spatial features that can be used to stratify operational model evaluation metrics and to test the extent to which the various modeling systems can replicate the features seen in the observations. Using a synoptic map typing approach, it is demonstrated that model performance varies with meteorological conditions associated with specific synoptic-scale flow patterns over both eastern NA and EU. For example, the root mean square error of simulated daily maximum 8-hr ozone was twice as high when cloud fractions were high compared with when cloud fractions were low over eastern NA. Furthermore, results show that over both NA and EU the regional models participating in AQMEII were able to better reproduce the observed variance in ambient ozone levels than the global model used to specify chemical boundary conditions, although the variance simulated by almost all regional models is still less that the observed variance on all spatiotemporal scales. In addition, all modeling systems showed poor correlations with observed fluctuations on the intraday time scale over both NA and EU. Furthermore, a methodology is introduced to distinguish between locally influenced and regionally representative sites for the purpose of model evaluation. Results reveal that all models have worse model performance at locally influenced sites. Overall, the analyses presented in this paper show how observed temporal and spatial information can be used to stratify operational model performance statistics and to test the modeling systems’ ability to replicate observed temporal and spatial features, especially at scales the modeling systems are designed to capture.
Implications: The analyses presented in this paper demonstrate how observed temporal and spatial information can be used to stratify operational model performance and to test the modeling systems’ ability to replicate observed temporal and spatial features. Decisions for the improvement of regional air quality models should be based on the information derived from only regionally representative sites. 相似文献
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Pratibha Sharma Manish Kumar N. Mathur A. Singh P. Bhatnagar M. Sogani 《Environmental science and pollution research international》2013,20(8):5160-5167
Health care waste includes all the waste generated by health care establishments, research facilities, and laboratories. This constitutes a variety of chemical substances, such as pharmaceuticals, radionuclides, solvents, and disinfectants. Recently, scientists and environmentalists have discovered that wastewater produced by hospitals possesses toxic properties due to various toxic chemicals and pharmaceuticals capable of causing environmental impacts and even lethal effects to organisms in aquatic ecosystems. Many of these compounds resist normal wastewater treatment and end up in surface waters. Besides aquatic organisms, humans can be exposed through drinking water produced from contaminated surface water. Indeed, some of the substances found in wastewaters are genotoxic and are suspected to be potential contributors to certain cancers. The aim of this study was to evaluate the genotoxic and cytotoxic potential of wastewaters from two hospitals and three clinical diagnostic centers located in Jaipur (Rajasthan State), India using the prokaryotic Salmonella mutagenicity assay (Ames assay) and the eukaryotic Saccharomyces cerevisiae respiration inhibition assay. In the Ames assay, untreated wastewaters from both of the health care sectors resulted in significantly increased numbers of revertant colonies up to 1,000–4,050 as measured by the Salmonella typhimurium TA98 and TA100 strains (with and without metabolic activation) after exposure to undiluted samples, which indicated the highly genotoxic nature of these wastewaters. Furthermore, both hospital and diagnostic samples were found to be highly cytotoxic. Effective concentrations at which 20 % (EC20) and 50 % (EC50) inhibition of the respiration rate of the cells occurred ranged between ~0.00 and 0.52 % and between 0.005 and 41.30 % (calculated with the help of the MS excel software XLSTAT 2012.1.01; Addinsoft), respectively, as determined by the S. cerevisiae assay. The results indicated that hospital wastewaters contain genotoxic and cytotoxic components. In addition, diagnostic centers also represent small but significant sources of genotoxic and cytotoxic wastes. 相似文献
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C. Kesavachandran B. S. Pangtey V. Bihari M. Fareed M. K. Pathak A. K. Srivastava N. Mathur 《Environmental monitoring and assessment》2013,185(2):1265-1272
The World Health Organization has estimated that air pollution is responsible for 1.4 % of all deaths and 0.8 % of disability-adjusted life years. NOIDA, located at the National Capital Region, India, was declared as one of the critically air-polluted areas by the Central Pollution Control Board of the Government of India. Studies on the relationship of reduction in lung functions of residents living in areas with higher concentrations of particulate matter (PM) in ambient air were inconclusive since the subjects of most of the studies are hospital admission cases. Very few studies, including one from India, have shown the relationship of PM concentration and its effects of lung functions in the same location. Hence, a cross-sectional study was undertaken to study the effect of particulate matter concentration in ambient air on the lung functions of residents living in a critically air-polluted area in India. PM concentrations in ambient air (PM1, PM2.5) were monitored at residential locations and identified locations with higher (NOIDA) and lower concentrations (Gurgaon). Lung function tests (FEV1, PEFR) were conducted using a spirometer in 757 residents. Both air monitoring and lung function tests were conducted on the same day. Significant negative linear relationship exists between higher concentrations of PM1 with reduced FEV1 and increased concentrations of PM2.5 with reduced PEFR and FEV1. The study shows that reductions in lung functions (PEFR and FEV1) can be attributed to higher particulate matter concentrations in ambient air. Decline in airflow obstruction in subjects exposed to high PM concentrations can be attributed to the fibrogenic response and associated airway wall remodeling. The study suggests the intervention of policy makers and stake holders to take necessary steps to reduce the emissions of PM concentrations, especially PM1, PM2.5, which can lead to serious respiratory health concerns in residents. 相似文献
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Brian Eder Daiwen Kang Rohit Mathur Jon Pleim Shaocai Yu Tanya Otte George Pouliot 《Atmospheric environment (Oxford, England : 1994)》2009,43(14):2312-2320
This paper provides a performance evaluation of the real-time, CONUS-scale National Air Quality Forecast Capability (NAQFC) that supported, in part, its transition into operational status. This evaluation focuses primarily on discrete forecasts for the maximum 8-h O3 concentrations covering the 4-month period, June through September, 2007, using measurements obtained from EPA's AIRNow network. Results indicate that the 2007 NAQFC performed as well or better than previous configurations, despite the expansion of the forecast domain into the western half of the nation that is dominated by complex terrain. The mean, domain-wide, season-long correlation was 0.70. When examined over time, the domain-wide correlations exhibit a fairly consistent nature, with values exceeding 0.60 (0.70) over 90% (55%) of the days. The NAQFC systematically over-predicted the 8-h O3 concentrations, continuing a trend established by earlier NAQFC configurations, though to a lesser degree. The summer-long mean forecast value of 53.2 ppb was 4.2 ppb higher than the observed value, resulting in a domain-wide Normalized Mean Bias (NMB) of 8.7%. Most of the over-prediction is associated with observed concentrations less than 50 ppb. In fact the model tends to under-predict when concentrations exceed 70 ppb. As with the bias, the error associated with the latest configuration was also lower. The summer-long Root Mean Square Error of 13.0 ppb (Normalized Mean Error (NME) = 20.4%) represented marked improvements over earlier forecasts. Examination of the spatial distribution of both the NMB and NME reveals that the NAQFC was generally within 25% for the NME and 25% for the NMB over a majority of the domain. Several areas of poorer performance, where the NMB and NME often exceed 25% and in some cases 50%, were noted. These areas include southern California, where the NAQFC tended to under-predict concentrations (especially on weekends) and the southeast Atlantic and Gulf coasts regions, where the model over-predicted. Subsequent analysis revealed that the incorrect temporal allocation of precursor emissions was likely the source of the under-prediction in southern California, while inaccurate simulation of PBL heights likely contributed to the over-prediction in the coastal regions. 相似文献
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