ABSTRACT
Metals and metalloids are toxic, persistent, and non-biodegradable and can be biomagnified (e.g., Hg), and therefore pose a serious threat to the algal flora of aquatic ecosystems. This laboratory study tested the effects of metals (Zn, Fe, and Hg) and a metalloid (As) on the cell wall morphology and protoplasmic content of living cells of six widespread diatom genera over 28 days. Diatoms exposed to Zn and Fe had a higher frequency of deformed diatom frustules (> 1%) compared to the As, Hg, and control treatments (< 1%). Deformities in the valve outline and striae were found in all treatments, including the control, whereas deformed raphes and more than one type of deformity were more prevalent under Zn and Hg stress. The order of toxicity is as follows: Zn > Fe > Hg≈As. Deformities were more frequent in Achnanthes and Diploneis (adnate forms) than in the motile genera of Nitzschia and Navicula. The correlation between the % healthy diatoms and % deformities in all six genera showed a negative relationship with the integrity of protoplasmic content (i.e., greater alteration in protoplasmic content was associated with greater frustule deformation). We conclude that diatom deformities can be a good indicator of metal and metalloid stress in waterbodies and are very useful in the rapid biomonitoring of aquatic ecosystems.
ABSTRACT
Presented herein is a data parsimonious model for identification of regional and local groundwater pollution sources at a reference time employing corresponding fields of head, concentration and its time derivative. The regional source flux, assumed to be uniformly distributed, is viewed as the causative factor for the widely prevalent background concentration. The localized concentration-excesses are attributed to flux from local sources distributed around the respective centroids. The groundwater pollution is parameterized by flux from regional and local sources, and distribution parameters of the latter. These parameters are estimated by minimizing the sum of squares of differences between the observed and simulated concentration fields. The concentration field is simulated by a numerical solution of the transient solute transport equation. The equation is solved assuming the temporal derivative term to be known a priori and merging it with the sink term. This strategy circumvents the requirement of dynamic concentration data. The head field is generated using discrete point head data employing a specially devised interpolator that controls the numerical-differentiation errors and simultaneously ensures micro-level mass balance. This measure eliminates the requirement of flow modeling without compromising the sanctity of head field. The model after due verification has been illustrated employing available and simulated data from an area lying between two rivers Yamuna and Krishni in India.
