A molecularly imprinted polymer (MIP) was synthesized using a polycyclic aromatic hydrocarbon (PAH) standard as a template, methacrylic acid as a functional monomer, ethylene glycol dimethacrylate as a cross-linker, and acetonitrile as a porogen. This polymer was used as a solid phase adsorbent for the quantitative enrichment of PAHs in coastal sediments, atmospheric particulates, and industrial effluents. The MIP selective adsorption capacity for PAHs started reducing when the chemical oxygen demand (COD) and total dissolved solids (TDS) was more than 800 mg L(-1) in the targeted environmental samples. The adsorption stability of the MIP was tested by the consecutive contact of environmental samples, and it was shown that the performance of the MIP did not vary after 10 enrichments and desorption cycles. Recoveries of eight PAH compounds, extracted from 10 g of coastal sediments and 1 L of industrial effluent spiked with 10 microL of standard PAHs, showed recoveries between 85 and 96%. The fluorescence spectrophotometer limit of detection of PAHs varied from 10 to 30 etag L(-1) in industrial effluent and from 0.1 to 2.9 etag kg(-1) in solid samples (coastal sediment and atmospheric particulates), and this indicates that the environmental analytical method is significantly sensitive, when compared with other commonly used methods such as gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry.
Noise mapping is a well-established practice among the European nations, and it has been follow for almost two decades. Recently, as per guidelines of the Directorate General of Mines Safety (DGMS), India, noise mapping has been made mandatory in the mining expanses. This study is an effort to map the noise levels in nearby areas of mines in the northern Keonjhar district. The motive of this study is to quantify the existing A-weighted time-average sound level (L Aeq, T ) in the study area to probe its effects on the human dwellings and noise sensitive areas with the probability of future development of the mines, roads, and industrial and commercial zone. The L Aeq, T was measured at 39 identified locations, including industrial, commercial, residential, and sensitive zones, 15 open cast mines, 3 major highways, and 3 haulage roads. With the utilisation of Predictor LimA Software and other GIS tools, the worked out data is mapped and noise contours are developed for the visualisation and identification of the extent and distribution of sound levels across the study area. This investigation discloses that the present noise level at 60% of the locations in silence and residential zone exposed to significantly high noise levels surpasses the prescribed limit of Central Pollution Control Board (CPCB), India. The observed day and night time L Aeq, T level of both zones ranged between 43.2-62.2 dB(A) and 30.5-53.4 dB(A), respectively, whereas, the average L dn values vary between 32.7 and 51.2 dB(A). The extensive mobility of heavy vehicles adjoining the sensitive areas and a nearby plethora of open cast mines is the leading cause of exceeded noise levels. The study divulges that the delicate establishments like schools and hospitals are susceptible to high noise levels throughout the day and night. A correlation between observed and software predicted values gives R 2 of 0.605 for L d , 0.217 for Ln, and 0.524 for L dn . Finally, the mitigation measure is proposed and demonstrated using a contour map showing a significant reduction in the noise levels by 0-5.3 dB(A).
The objective of this study is to develop a traffic noise model under diverse traffic conditions in metropolitan cities. The model has been developed to calculate equivalent traffic noise based on four input variables i.e. equivalent traffic flow (Q e ), equivalent vehicle speed (S e ) and distance (d) and honking (h). The traffic data is collected and statistically analyzed in three different cases for 15-min during morning and evening rush hours. Case I represents congested traffic where equivalent vehicle speed is <30 km/h while case II represents free-flowing traffic where equivalent vehicle speed is >30 km/h and case III represents calm traffic where no honking is recorded. The noise model showed better results than earlier developed noise model for Indian traffic conditions. A comparative assessment between present and earlier developed noise model has also been presented in the study. The model is validated with measured noise levels and the correlation coefficients between measured and predicted noise levels were found to be 0.75, 0.83 and 0.86 for case I, II and III respectively. The noise model performs reasonably well under different traffic conditions and could be implemented for traffic noise prediction at other region as well.
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