Ecological risk evaluation and source apportionment of heavy metals in park playgrounds: a case study in Xi’an, Shaanxi Province, a northwest city of China

Guo, Bin; Su, Yi; Pei, Lin; Wang, Xiaofeng; Zhang, Bo; Zhang, Dingming; Wang, Xiaoxia

Ecological risk evaluation and source apportionment of heavy metals in park playgrounds: a case study in Xi’an, Shaanxi Province, a northwest city of China

2020

Park playgrounds recently are suffering serious heavy metals contamination in China. It is urgent to assess the ecological risk and identify the sources for heavy metals. A total of 111 topsoil samples were collected from four park playgrounds in Xi’an, and the X-ray fluorescence (XRF) instrument was used to measure the concentrations of heavy metals including chromium(Cr), nickel (Ni), copper (Cu), zinc (Zn), arsenic (As), lead (Pb), manganese (Mn), and cobalt (Co), respectively. Ecological risk ([Formula: see text]) and potential ecological risk index (RI) were introduced to determine the pollution level and ecological risk, and the absolute principal component score-multiple linear regression (APCS-MLR) model was implemented to identify the sources for heavy metals. The main results were as follows. (1) Except As, the mean concentrations of measured heavy metals of four park playgrounds surpassed the soil background values of Shaanxi Province. (2) In each park playground, the [Formula: see text] was below a “low” risk level ([Formula: see text]=10) for Cr, Ni, Zn, As, and Mn; Cu was between a “moderate” and “considerable” risk level; Pb was between a “low” and “moderate” risk level; and [Formula: see text] was between a “considerable” and “high” risk level for Co. Besides, the RI index was on a “high” risk level (120 < RI < 240) with an obvious spatial distinction. (3) The anthropogenic factors were the main sources for heavy metals, and mixed sources and natural sources were considered as the minor sources for metals. (4) The sources contributions for Co had obvious spatial heterogeneity in each park situated in four different urban planning districts.

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