No abstract

The positive matrix factorization (PMF) receptor model was used for the first time to quantify the source contributions to heavy metal pollution of sediment on a national basin scale in the upstream, midstream, and downstream rivers (Teesta and Kortoya-Shitalakkah and Meghna-Rupsha and Pasur) of Bangladesh. The metal contamination status, cooccurrence, and ecotoxicological risk were also investigated. Sediment samples were collected from 30 sites at a depth range of 0 to 20 cm for analysis of 9 metals using inductively coupled plasma-mass spectrometry. The mean concentrations of metals varied for upstream, lower midstream, and downstream river segments. The results showed that chromium (Cr) exhibited a strong significant co-occurrence network with other metals (e.g., manganese [Mn], iron [Fe], and nickel [Ni]). Monte Carlo simulation results of the geo-accumulation index (Igeo; 63.3%) and risk indices (48.5%) showed that cadmium (Cd) was the main contributor to sediment pollution. However, the cumulative probabilities of sediments being polluted by metals were ranked as "moderate to heavily polluted" (Igeo 46.6%; risk index 16.7%). Toxicity unit results revealed that zinc (Zn) and Cd were the key toxic contributors to sediments. The PMF model predicted metal concentrations and identified 4 potential sources. The agricultural source (factor 1) mostly contributed to copper (Cu; 78.9%) and arsenic (As; 62.8%); Ni (96.9%) and Mn (83.5%) exhibited industrial point sources (factor 2), with 2 hot spots in northwestern and southwestern regions. Cadmium (93.5%) had anthropogenic point sources (factor 3), and Fe (64.3%) and Cr (53.5%) had a mixed source (factor 4). Spatially, similar patterns between PMF apportioning factors and predicted metal sources were identified, showing the efficiency of the model for river systems analysis. The degree of metal contamination in the river segments suggests an alarming condition for biotic components of the ecosystem.

No abstract

Coal-fly-ash is one of the major byproducts of coal-based power plant in which naturally occurring radioactive materials (NORMs) are drastically enriched compared to those of feed coals. Thus, improper management of fly-ash may introduce additional radioactivity to the surrounding environment and cause radiological risk. So, in order to study the distribution of radionuclides in soil around a coal-based power plant and to evaluate their radiological risk, soil, coal and fly-ash samples were analyzed by using a HPGe detector for U-238, Ra-226, Th-232 and K-40 radioactivity concentrations. Furthermore, soil minerals were also studied by X-ray diffractometer to assess the mineralogical provenance of the radionuclides. Mean radioactivity concentrations (in Bq·kg−1) of U-238, Ra-226, Th-232 and K-40 in soil samples are 102.9±41.4, 63.6±7.4, 103.4±13.9 and 494.2±107.5, respectively which are comparatively higher than the typical world mean value. Elevated levels of radioactivity are likely due to the presence of illite, kaolinite, monazite, rutile and zircon minerals in the soil samples rather than technogenic contributions from the power plant. Furthermore, mean soil contamination factor (CF) are close to unity and mean pollution load index (PLI) is below unity while the average radium equivalent activity (Raeq in Bq·kg−1), external hazard index (Hex), absorbed γ dose rate (D in nGyh−1), annual effective dose rate (E in mSv·y−1) and excess lifetime cancer risk (ELCR in Sv−1) are 249.5±21.7, 0.67±0.06, 114.2±9.4, 0.20±0.02, 4.9×10−4±0.4×10−4, respectively, which are within the permissible limit. Thus, in terms of radioactivity concentrations and associated environmental and radiological indices, the effect of the power plant is insignificant.

No abstract