Reconstruction of atmospheric concentrations and deposition of uranium and decay products released from the former uranium mill at Uravan, Colorado

Radionuclide concentrations in air from uranium milling emissions were estimated for the town of Uravan, Colorado, USA and the surrounding area for a 49-yr period of mill operations beginning in 1936 and ending in 1984. Milling processes with the potential to emit radionuclides to the air included crushing and grinding of ores; conveyance of ore; ore roasting, drying, and packaging of the product (U(3)O(8)); and fugitive dust releases from ore piles, tailings' piles, and roads. The town of Uravan is located in a narrow canyon formed by the San Miguel River in western Colorado. Atmospheric transport modeling required a complex terrain model. Because historical meteorological data necessary for a complex terrain model were lacking, meteorological instruments were installed, and relevant data were collected for 1 yr. Monthly average dispersion and deposition factors were calculated using the complex terrain model, CALPUFF. Radionuclide concentrations in air and deposition on ground were calculated by multiplying the estimated source-specific release rate by the dispersion or deposition factor. Time-dependent resuspension was also included in the model. Predicted concentrations in air and soil were compared to measurements from continuous air samplers from 1979 to 1986 and to soil profile sampling performed in 2006. The geometric mean predicted-to-observed ratio for annual average air concentrations was 1.25 with a geometric standard deviation of 1.8. Predicted-to-observed ratios for uranium concentrations in undisturbed soil ranged from 0.67 to 1.22. Average air concentrations from 1936 to 1984 in housing blocks ranged from about 2.5 to 6 mBq m(-3) for (238)U and 1.5 to 3.5 mBq m(-3) for (230)Th, (226)Ra, and (210)Pb.     

Nutrient and trace elements in soil and desert vegetation of southern Idaho

Concentrations of thirty elements were measured in strong-acid extracts of soil, sagebrush (Artemisia tridentata spp.) leaves and perennial grass from the Idaho National Engineering Laboratory (INEL) and two reference sites in southern Idaho. A bicarbonate-chelating extract of soil was used to estimate plant-available concentrations. The results provide baseline data prior to start-up of a coal-fired steam generation facility on the INEL and other developments in the region. In addition, existing impact from effluents from thirty years of a nuclear fuel reprocessing facility on the INEL was evaluated. Based on the spatial distribution of element concentrations, as well as comparison with references sites, we conclude that concentrations of Zn, and perhaps Ni, Cd, and V, are currently elevated around the fuel reprocessing facility. The spatial distribution of these elements is similar to that of ¹³⁷Cs in soil, a radionuclide which is emitted by the facility. Sagebrush and soil appear more responsive than perennial grass for long-term monitoring of element concentrations in this semi-arid environment.     

Green supply chain management in the chemical industry: structural framework of drivers

ABSTRACT

The main purpose of Green Supply Chain Management (GSCM) is to improve the quality of supply chain management strategies and environmental performance. As per current statistics, the chemical industry is growing fast in Bangladesh. In order to compete for global competition, GSCM is essential in this sector. This paper proposes a systematic approach of structural framework whose aim is to enhance the probability of constructive implementation of GSCM in the field chemical industry in Bangladesh. Therefore, this framework evaluates the appropriate interrelationship along with the drivers of GSCM in the chemical industry. In total, eight drivers were finalized from an associated literature review with the help of survey and by taking expert opinions via the Delphi methodology. In addition to MICMAC analysis, the driving and the dependence powers for all the drivers were determined. Moreover, the structural frameworks for the drivers were developed by means of total interpretive structural modeling (TISM) technique. As a result, the findings indicate that the most significant driver was supplier pressure and willingness and the most important barrier was high cost. Finally, the main objective of this research is expected to help industrial managers to evaluate and understand the critical areas where they should emphasize to implement GSCM in the chemical industry.