DOI: 10.5061/dryad.mkkwh7150
title: Distribution of heavy metals in coastal sediments under the influence of multiple factors: A case study from the south coast of an industrialized harbor city (Tangshan, China)

description: This research investigated the spatial distribution of heavy metals,
 including mercury (Hg), cadmium (Cd), copper (Cu), arsenic (As), nickel
 (Ni), lead (Pb), chromium (Cr), and zinc (Zn), in surface sediments from
 the coastal area near to an industrial harbor (the Tangshan Harbor, China)
 with 161 sediment samples. The results showed that the distribution
 patterns of Cr, Cu, Zn, Ni, and Pb were similar to each other, high in the
 northwest, southeast, and southwest regions of the study area and low in
 the northeast region, which corresponded well with components of
 sedimental sizes. The uncontaminated specimen proportions for Hg, Cd, Cu,
 As, Ni, Pb, Cr, and Zn were 6.8%, 4.3%, 31.1%, 28.6%, 42.9%, 64.6%, 44.7%,
 and 50.3%, respectively. Based on principal component analysis (PCA) and
 positive matrix factorization (PMF), four distinct sources of pollution
 were quantitatively attributed, including agricultural activities
 (22.08%), fossil fuel consumption (24.14%), steel production (29.78%), and
 natural sources (24.00%). Hg (80.29%), Cd (82.31%) and As (65.33%) in the
 region’s coastal sediments were predominantly contributed by fossil fuel,
 steel production and agricultural sources, respectively. Cr (40.00%), Cu
 (43.63%), Ni (47.54%), and Zn (38.98%) were primarily of natural
 lithogenic origin, while Pb mainly came from the mixed sources of
 agricultural activities (36.63%), fossil fuel (36.86%), and steel
 production (34.35%). Multiple factors played important roles in the
 selective transportation of sedimentary heavy metals, especially sediment
 properties, and hydrodynamic sorting processes in the study area.
description: <strong>Study area and
 sampling sites</strong> As a shallow semi-enclosed epicontinental sea,
 the Bohai Sea received large amounts of terrestrial matter from coastal
 rivers, especially the Yellow River, which predominates in sediment
 transportation (Wang et al., 2014; Liu et al., 2020).
 There are several coastal rivers
 flowing into the study area with large amounts of sand, such as the Haihe
 River, the Jiyunhe River, the Daqinghe River, the Luanhe River, the Liaohe
 River, and the Yellow River. Heavy metals within sediments were redistributed
 by currents in the area. The relatively warm and saline Yellow Sea Warm
 Current (YSWC) flows into the Bohai Sea from the Yellow Sea in winter (Xu
 et al. 2009). The North
 Shandong Coastal Current (NSCC) originates from the west coast of Bohai
 Bay and flows along the northern coast of the Shandong Peninsula in winter
 and summer (Fig. 1; Yuan et al., 2020). The main tidal constituent in the
 Bohai Sea is the semi-diurnal tidal component M2 with an average amplitude
 of 2 m (Li et al., 2019). A total of 161 surface sediment samples (0~2 cm
 depth) collected from the south coast of Tangshan city in September and
 October 2021 were analyzed in this study (Fig. 1). These samples were
 distributed evenly across the study area and obtained with a stainless
 steel grab sampler dropped from a sampling ship. After the sediments were
 retrieved, the samples were placed in a sterile bag with a resealable
 zipper and stored at 4 °C in the dark until further analyses in the
 laboratory. <strong>Grain size
 analyses</strong> The organic and calcareous matters in each
 sample were removed by treatment with 30% H2O2 and 10% HCl. Before
 analysis, 0.5 M (NaPO3)6 was used to ensure complete disaggregation under
 ultrasonic dispersion. A laser particle size analyzer (Anton Paar PSA1190,
 Austria) was used for measuring sediment grain sizes in duplicate, with
 differences between measurements at &lt; 1%. The percentages of clay,
 silt, and sand were determined with the grain size groups of &lt;4 mm,
 4~63 mm, and &gt;63 mm, respectively. And the grain size parameter
 calculations were referred to a previous literature (Folk and Ward,
 1957). <strong>Heavy metals
 analyses</strong> <em>1. Cu, Cr, Zn, Pb, Ni, Cd, and
 As </em> The sample was dried at 110°C for 5 hours,
 ground and sieved through a 200-mesh nylon sieve. A suitable amount of the
 sample was weighed and placed in a polytetrafluoroethylene sealed
 extraction vessel, followed by adding 1 ml of nitric acid and 3 ml of
 hydrofluoric acid. The mixture was shaken well and sealed tightly. The
 sealed vessel was subjected to thermal decomposition at 160°C~180°C for 48
 hours using an automatic temperature-controlled hotplate. After cooling,
 the vessel was opened and the sample was steamed until nearly dry before
 adding 1 ml of perchloric acid. The sample was further steamed until fumes
 of white smoke appeared. After cooling, 2 ml of hydrochloric acid was
 added and the mixture was heated on an automatic temperature-controlled
 hotplate until the salt dissolved. The sample was then steamed until
 nearly dry before adding 2 ml of nitric acid to remove chloride ions.
 Next, 1.5 ml of nitric acid was added, the vessel was sealed tightly and
 heated to dissolve the sample for 12 hours at 160°C ~180°C on an automatic
 temperature-controlled hotplate. After cooling, the vessel was opened, and
 an appropriate amount of internal standard solution was added. The mixture
 was shaken well and held at 80°C for 12 hours on an automatic
 temperature-controlled hotplate. After cooling to room temperature, the
 vessel was opened, and the sample was transferred to a 50 ml volumetric
 flask with nitric acid and diluted to the mark. The contents were mixed
 well, and the levels of Cu, Cr, Zn, Pb, Ni, Cd, and As were determined
 using inductively coupled plasma mass spectrometry.
 During
 the testing process, parallel analysis was carried out on 10% of the
 samples and two blank samples were included. The pass rate of the parallel
 samples was 100%, and the blank samples were all below the detection limit
 of the method. The results were validated using National Standard
 Materials of China (GBW07314, GBW07315, GBW07316), and the test values
 were within the standard value range.
 <em>2.
 Hg</em> The sample was dried at 110°C for 5 hours,
 ground and passed through a 200-mesh nylon sieve. An accurate amount of
 the sample was weighed and placed in a 50 ml stoppered colorimetric tube.
 To the tube, 2ml of nitric acid and 6ml of hydrochloric acid were added.
 Approximately 10ml of deionized water was used to rinse the inner wall of
 the tube thoroughly, and the mixture was stirred well. The tube was heated
 in a boiling water bath for 1 hour (with adequate shaking once during this
 process). The tube was removed and allowed to cool to room temperature, to
 which 1ml of potassium permanganate solution was added. The solution was
 shaken well for 20 minutes and then diluted with oxalic acid solution to
 the calibration mark. After thorough agitation, the tube was left standing
 to settle for 30 minutes. The determination of Hg was carried out using
 atomic fluorescence spectrometry. During the testing process, 10% parallel sample
 analyses and two sample blanks were conducted for each batch of samples.
 The qualification rate of parallel samples was 100%, and the sample blanks
 were less than the detection limit of the method. Validation was conducted
 using National Standard Substances of China (GBW07314 and GBW07316), and
 the test values were within the range of standard
 values. <em>3. aluminum
 (Al)</em> To accurately weigh the rock powder sample dried
 at 105°C, 4g of sample was weighed with precision to 0.01g. The sample was
 transferred to a press mold, and boric acid was added for edge wrapping
 (press pressure of 30 MPa, held for 3s). The resulting pressed sample had
 a flat surface, and residual powder on the sample surface was blown away
 with an ear syringe. The sample was marked with a sample number and
 prepared for machine testing. The ZSX Primus II X-ray fluorescence
 spectrometer from Japan was used for testing the Al2O3
 content. During the testing process, 10% parallel sample
 analyses were conducted for each batch of samples. The qualification rate
 of parallel samples was 100%. Validation was conducted using National
 Standard Substances of China (GSD-10, GSD-11, GSD-12), and the test values
 were within the range of standard values.
 In addition, the measurement
 error of the replicate sediments was within 5%. The Method Limit of
 detection were 0.07, 1.0, 0.2, 2.0, 1.0, 0.02, 0.1, and 0.002 mg kg–1
 for Cr, Ni, Cu, Zn, As, Cd, Pb, and Hg, respectively. The
 Limit of quantitation were
 0.28, 4.0,
 0.8, 8.0, 4.0, 0.08, 0.4, and 0.008 mg kg–1 for Cr, Ni, Cu, Zn, As, Cd, Pb,
 and Hg, respectively. <em>4. Statistical
 analyses</em> As a classical assessment model, the
 Geo-accumulation index (Igeo) was widely used to assess the contamination
 extent of heavy metals in surface sediments by comparing the current
 concentrations with pre-industrial levels (Müller, 1979). The Igeos of the
 heavy metals were determined for analyzing the sources of heavy metals and
 understanding the heavy metal enrichment in the sediments near the study
 harbor, which were defined by the following
 equation: Igeo = log2
 (Metalsample/1.5Metalbackground) where 1.5 serves as a correction factor to
 balance the variation of background values caused by diagenesis and the
 Metalbackground is the background geochemical values of the heavy elements
 (Sharifuzzaman et al., 2016). The enrichment factor (EF) was used to evaluate
 anthropogenic influences of heavy metals in sediments because it can
 distinguish the sources of the metals from natural weathering processes
 and anthropogenic activities and display the status of environmental
 contamination (Zhang et al., 2007). As a conserved element, Al (Fig. S1)
 was used in calculating the enrichment factor for its standardization and
 elimination of the grain size effect (Fan et al., 2022). Referring to the
 previous literature (Buat-Menard and Chesselet, 1979), the EF was
 calculated as follows: EF
 =(Metal/Al)sample/(Metal/Al)background
 where (Metal/Al)background was
 calculated according to a previous reference (Zhao and Yan, 1994).
 Non-crustal sources of the heavy metals were corresponding to EF of
 &gt;1.5, which were also thought to be related to human activities
 (Zhang et al., 2007). The ecological effects of heavy metals were
 assessed by Effects range-low (ERL) and Effects range-mean (ERM), which
 represented the occasional occurrence of adverse biological effects (Long
 et al., 1995). As an effective method to analyze the sources of
 heavy metals, the PCA was used in an attempt to further clarify the
 contribution of heavy metals in the sediments near the harbor (Liu et al.,
 2016a; Ogunlaja et al., 2019). In this analysis, we used the eight heavy
 metals as variables for PCA. The Kaiser-Meyer-Olkin-Measure of Sampling
 Adequacy (KMO) was 0.885 (&gt; 0.6) and the significance level was
 zero (&lt; 0.05), meaning suitable data for
 PCA. The PMF model decomposes the original matrix
 into a contribution matrix and a factor allocation matrix to conduct data
 analysis, while also quantitatively describing the contribution of each
 sample (Jiang et al., 2017; Jiang et al., 2020). The computation principles and formula
 pertaining to PMF were derived from a scholarly work (Huang et al., 2022a,
 2022b). A Gao-Collins grain-size trends analysis (GSTA)
 method to produce a grain size trend map of the study area based on the
 spatial distribution of the grain size distributions (Gao and Collins,
 2001). The GSTA exported the vector characteristics (magnitude and length)
 to deduct the vector pattern for the complete grain-size distribution,
 just as in the previous study (Gao, 1996; Lv et al.,
 2021).