A GFP-based bacterial biosensor with chromosomally integrated sensing cassette for quantitative detection of Hg(II) in environment

A mercury biosensor was constructed by integrating biosensor genetic elements into E. coli JM109 chromosome in a single copy number, using the attP/attB recombination mechanism of λphage. The genetic elements used include a regulatory protein gene (merR) along with operator/promoter (O/P) derived from the mercury resistance operon from pDU1358 plasmid of Serratia marcescens. The expression of reporter gene gfp is also controlled by merR/O/P. Integration of the construct into the chromosome was done to increase the stability and precision of the biosensor. This biosensor could detect Hg(II) ions in the concentration range of 100-1700 nmol/L, and manifest the result as the expression of GFP. The GFP expression was significantly different (P ≤ 0.05) for each concentration of inducing Hg(II) ions in the detection range, which reduces the chances of misinterpretation of results. A model using regression method was also derived for the quantification of the concentration of Hg(II) in water samples.     

Fluorometric detection of bisphenol A using β-cyclodextrin-functionalized ZnO QDs

Environmental Science and Pollution Research - The estrogenic property of bisphenol A (BPA) leads to potential adverse health and ecological effects. A simple, selective, and cost-effective sensor...     

Remote sensing of atmospheric aerosol in the nocturnal boundary layer using lidar

This paper presents the results of the lidar experiments that have been performed during January 1989 through August 1990 to study the aerosol vertical distributions in the nocturnal atmosphere and their comparison with near-simultaneous aerological soundings for environmental monitoring. During the study period, the aerosol distributions showed significant stratified aerosol layer structures in the lower atmosphere throughout the south-west monsoon season (June-September), while these structures appear to be either erratic or absent during remaining months of the year. In addition, the aerosols present in the lowest air layers up to 200 m are found to contribute significantly (about 40%) to the aerosol loading in the nocturnal boundary layer at the lidar site. The pre-monsoon to winter ratio of mixing depth and ventilation coefficient were found to be 1.11 and 1.62, respectively. Thus the height of the mixed layer (around 350 m) and the associated ventilation coefficients suggest that early winter evenings tend to have higher pollution potential at the experimental site. The results indicate that the lidar technique has the potential to yield good information on the structure of the nocturnal atmosphere which is found to be influenced by the atmospheric stability conditions as revealed by aerological observations.     

A Power Law Model for River Flow Velocity in Iowa Basins

This study explores power law relationships to estimate water flow velocity as a function of discharge and drainage area across river networks. We test the model using empirical data from 214 United States (U.S.) Geological Survey gauging stations distributed over the state of Iowa in the U.S. The empirical data are the measurements of the mean cross‐sectional velocity and concurrent discharge. The data are used to estimate parameters for a state‐wide model and to test for spatial variability for 15 large river basins contained within the state. Spatial differences among the basins are small but some parameters significantly differ from the state‐wide model. Using individual station data, the authors also explore a simpler power law model that disregards dependence on the drainage area. Overall, the study shows that including drainage area improves the model. Our study provides parameter values that can be directly incorporated into a regional scale routing model, and provides a framework for developing flow velocity models for hydraulically similar rivers in the U.S. and the world.     

Identification and elucidation of anthropogenic source contribution in PM10 pollutant: Insight gain from dispersion and receptor models

Source apportionment study of PM₁₀ (Particulate Matter) in a critically polluted area of Jharia coalfield, India has been carried out using Dispersion model, Principle Component Analysis (PCA) and Chemical Mass Balance (CMB) techniques. Dispersion model Atmospheric Dispersion Model (AERMOD) was introduced to simplify the complexity of sources in Jharia coalfield. PCA and CMB analysis indicates that monitoring stations near the mining area were mainly affected by the emission from open coal mining and its associated activities such as coal transportation, loading and unloading of coal. Mine fire emission also contributed a considerable amount of particulate matters in monitoring stations. Locations in the city area were mostly affected by vehicular, Liquid Petroleum Gas (LPG) & Diesel Generator (DG) set emissions, residential, and commercial activities. The experimental data sampling and their analysis could aid understanding how dispersion based model technique along with receptor model based concept can be strategically used for quantitative analysis of Natural and Anthropogenic sources of PM₁₀.