Atmospheric Heavy Metals Biomonitoring Using a Local Pinus eldarica Tree

Abstract

Background: Trees are one of the most commonly used bio-indicators and have been widely applied for heavy metals (HMs) monitoring in the ambient air because of their simple and efficient sampling and examination. Objectives: The main objective of this study was to evaluate local pine trees for their potential as a bio-indicator of HMs in urban areas. Besides, the distribution pattern of HMs in the study area, meteorological and land use factors affecting this pattern, and HMs source identification were investigated. Methods: Forty-eight sampling locations were selected in the Yazd city, capital of Yazd province in Iran, and concentrations of five HMs- iron (Fe), copper (Cu), zinc (Zn), lead (Pb), and cadmium (Cd)- were measured in the leaves of the most abundantly local pine trees, Pinus eldarica, using the atomic absorption spectroscopy method. The obtained data were analyzed for source identification using Spearman’s rank correlation coefficient and principal component analysis (PCA). The ordinary Kriging method was used to obtain a spatial map of HMs distribution in the study area. Results: Iron had the highest concentration (345.0053 mg/kg) in leaves when compared with other HMs. The concentration of Zn, Cu, Pb and Cd were 26.1384, 5.5905, 2.9963 and 0.7383 mg/kg, respectively. Spatial mapping indicated that industrial districts and areas with heavy traffic had the highest HMs pollution. Wind direction was recognized to be the most important factor in HMs transportation. Anthropogenic sources were known as the main responsible factor for HMs emission. Conclusions: Pine trees can be used as a worthy bio-indicator for HMs pollution monitoring in the ambient air in areas with extensive vegetation of pine trees.