Determining the Contribution of Nearby Power Plants to Deposited Foliar Dust: A Case Study of BTPS, Bokaro.

Abstract

Deposition of dust particles on foliage surfaces helps to filter airborne dust particles that occur predominantly in areas near thermal power plants (TPPs). Highly dust-laden foliage surrounding TPPs is a serious issue affecting the vegetation and façade greening adversely. Fly ash (FA) generated by TPPs have an adverse impact on the growth and development of flora. Therefore, identification of their percentage contribution on foliar dust (FD) is of utmost importance. The present study attempted to identify all the contributing sources to FD. Morphological and chemical characterization of FD, FA, and road dust (RD) has been evaluated, followed by their multivariate statistical analysis. Contamination of FD from different sources was estimated by using field emission scanning electron microscope (FE-SEM) coupled with energy dispersive X-ray technique (EDX), Fourier transform infrared spectroscope (FTIR), and atomic absorption spectrophotometer techniques. Particle size distribution of FD revealed that the major portion of FD was <2µm. FE-SEM and EDX analysis confirmed contamination of FD by FA, resuspension of RD, and local sources. FTIR peaks depicted the presence of different functional groups, including silica from nearby roads, saturated-nonsaturated, and aromatic organic functional groups originating predominantly from different activities of TPPs and traffic. Results of IR were in agreement with results obtained in physicochemical analyses. Heavy metals analysis of FA demonstrated high concentration of carcinogens Cr, Cu, Cd, and Ni and could be considered a marker to them. Certain heavy metals (Fe, Co, Mn, Pb, and Zn) were found to be in the order RD>FA>FD. This explores the necessity for considering other sources other than TPP sources. Principal component analysis (PCA) of heavy metals present in FD revealed that the sampling area was chiefly influenced from three sources: Bokaro thermal power station (55%), RD (18%), and local sources (27%). Cluster analysis complemented the results of Pearson correlation matrix and PCA. Analyses illustrated the substantial influence of TPPs along with other source's significance in contamination of FD.