Characteristics and health risk assessment of heavy metals exposure via household dust from urban area in Chengdu, China

Science of the Total Environment 619–620 (2018) 621–629

Contents lists available at ScienceDirect

Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv

Characteristics and health risk assessment of heavy metals exposure via household dust from urban area in Chengdu, China Zhang Cheng a,⁎,1, Liu-Jun Chen a,1, Han-Han Li a,1, Jian-Qing Lin b,1, Zhan-Biao Yang a, Yuan-Xiang Yang a, Xiao-Xun Xu a, Jun-Ren Xian a, Ji-Rong Shao c, Xue-Mei Zhu a,⁎ a b c

College of Environment, Sichuan Agricultural University, Chengdu 611130, China Department of Environmental Engineering, College of Food and Biological Engineering, Jimei University, Xiamen 361021, China School of Life Sciences, Sichuan Agricultural University, Yaan 625014, China

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• Heavy metal concentrations in household dust collected from 6 urban districts. • Health risks were evaluated for the metals combined with oral bioaccessibility. • There was negative correlation between the metals concentrations and floor levels.

a r t i c l e

i n f o

Article history: Received 23 August 2017 Received in revised form 13 November 2017 Accepted 13 November 2017 Available online xxxx Editor: F. M. Tack Keywords: Urban household dust Heavy metals Bioaccessible Risk assessment

a b s t r a c t To investigate the characteristics of heavy metals (Cr, Cd, Pb, Zn, Cu and Ni) in household dust in urban household environment of Chengdu, China, 90 household dust samples were collected from 6 districts of the city. The information of houses and residents were also recorded during dust sampling to identify the correlations between heavy metals in household dust and the house attributes. And also the principal component analysis and cluster analysis for sources and impactor factors. The concentrations of Pb (123 mg·kg−1), Zn (675 mg·kg−1), Cu (190 mg·kg−1), Cr (82.7 mg·kg−1), Cd (2.37 mg·kg−1) and Ni (52.6 mg·kg−1) in household dust are in low or moderate levels when compare with that from other counties or areas. The heavy metals of household dust samples from Chengdu is higher concentrations than that in the street dust from Chengdu, except for Cr. Statistical analysis result showed traffic sources and corrosion of alloys are important factors contributing to the rise concentrations of heavy metals in household dust. In addition, there is negative correlation (p b 0.05) between the heavy metals concentrations and floor levels. The ingestion is the important pathway for Pb, Zn, Cu and Ni via household dust exposure to the residents, and the dermal contact was identified as a main route for Cr and Cd in household dust exposure to the residents. There are minor non-carcinogenic and carcinogenic risks from the heavy metals in household dust for the residents in Chengdu. © 2017 Elsevier B.V. All rights reserved.

⁎ Corresponding author. E-mail addresses: [email protected] (Z. Cheng), [email protected] (X.-M. Zhu). 1 These authors contributed equally to this work.

https://doi.org/10.1016/j.scitotenv.2017.11.144 0048-9697/© 2017 Elsevier B.V. All rights reserved.

622

Z. Cheng et al. / Science of the Total Environment 619–620 (2018) 621–629

1. Introduction Urban dust as sink and source of air pollution, which can indicate the characteristics of heavy metals distribution and accumulation in urban environment (Hu et al., 2011; Huang et al., 2014c; Wei and Yang, 2010). Household dust is heterogeneous and complex mixture of organic and inorganic particles (Maertens et al., 2004), which could absorb and accumulate heavy metals (eg: lead, Pb; zinc, Zn; copper, Cu; chromium, Cr; nickel, Ni; cadmium, Cd) (Rasmussen, 2004). It is reported that adults and children have approximately 88% and 75% of the day time stay at indoor environment, respectively (US EPA, 1997). Therefore, household dust maybe a major pathway of heavy metals exposure to the residents (Hassan, 2012; Hogervorst et al., 2007; Yoshinaga et al., 2014). In recent years, the content of heavy metal in household dust has become the focus of social concern (He et al., 2017; Li et al., 2014; Olujimi et al., 2015). Previous studies indicated there were two major way of heavy metals from the outdoor to the indoor: the soil or dust that stick to footwear is brought into room, and the suspended particulate matter in outdoor air drift in house (Hunt et al., 2006; Thatcher and Layton, 1995). The soil and outdoor dust in residential area could be enriched heavy metals by anthropogenic activities (vehicular traffic, industrial plants, city construction) and other activities with the process of urbanization (Wang et al., 2016; Wei et al., 2015). In addition, the number of storey and height of the building, the frequency and time of windows opened, the number of residents and pets in house could also affect to the concentrations of heavy metals in household dust (Kurt-Karakus, 2012). On the other hand, the household environment and activities are also the important factors which can affect the content of heavy metals in household. Previous studies showed the color of the wall paints was an important source of heavy metals in household dust, eg, yellow color was connected with the relative higher concentrations of Cd, Cu, Pb, and Zn, purple paint was correlated with the higher levels of Zn and Pb and green paint had elevated the content of Cu (Chattopadhyay et al., 2003; Tong and Lam, 2000). The daily fuel combustion for domestic cooking play also a crucial factor on the heavy metals accumulated in household dust (Hassan, 2000). Furthermore, heavy metals in household dust also related to smoking, sweeping frequency, the use of air conditioning and rubber carpet products, paint and cooking frequency (Kim and Fergusson, 1993; Kurt-Karakus, 2012; Rasmussen et al., 2013). However, the living habits of residents in different countries and areas are vary greatly, the data of questionnaire and correspondingly analyzed with the statistical methods could reflect more reliable relationship between the household attributes and heavy metals concentration in household dust from the study area. In recent years, lots of studies on heavy metals in indoor dust were focused on concentrations, source, particle diameter, spatial characteristics and pollution assessment (Akinwunmi et al., 2017; He et al., 2017; Olujimi et al., 2015). The results showed dust which b 63 μm in particle size can be easily re-suspended into atmosphere and have a higher tendency to absorb by humans via ingestion, inhalation and dermal adsorption than the dust in other particle size (Mohmand et al., 2015; Shilton et al., 2005; Zheng et al., 2010). In addition, the fine particles dust also have relatively high surface area and were detected higher concentrations of heavy metals (Hassan, 2012). Therefore, the fine particles dust is the research focus of heavy metals in household dust. Due to the toxicity, persistence and bioaccumulation, long-term exposure to heavy metals contaminated dust can affect the human health. Pb has a half-life of 4 years in the human body, and up to 10 years in the bones, and Pb is found to be destructive to the nervous system, kidney, circulatory and reproductive systems, especially for children (Needleman, 2009). The half-life of Cd is 6.2 to 18 years in the human body, and Cd is also neurotoxic for living organisms including humans, and toxic to kidney (Thomas et al., 2009). Zn and Cu are essential element for human, but they are initiators or promoters of carcinogenic activities in animals (Nriagu, 1988). Health risk assessment of exposure

to heavy metals in indoor dust has been attempted in lots of cities in the world, such as Istanbul, Turkey (Kurt-Karakus, 2012), Lahore and Sargodha, Pakistan (Mohmand et al., 2015), Japan (Yoshinaga et al., 2014), Ogun State, Nigeria (Olujimi et al., 2015), Rouen, France (Marcotte et al., 2017), Guangzhou, China (Huang et al., 2014c). In general, the studies showed that oral ingestion is the primary exposure route to household dust for humans, compared with inhalation and dermal contact. The ingested dusts reach the gastrointestinal tract where heavy metals are partly dissolved (Butte and Heinzow, 2002), then heavy metal are transported by the circulatory system and finally accumulated in tissues and organs of the human body. Physiologically based extraction test (PBET), an in-vitro gastrointestinal method, has been widely applied to assess the bioaccessibility of heavy metals in the stomach and intestinal tract (Turner and Hefzi, 2010; Turner and Ip, 2007). However, there are few studies on the health risks associated with the actual situation of the local resident (eg: exposure frequency, exposure duration, body weight). Chengdu, as a large central city in China, has an urban population of 15.7 million in 2015 and a huge of living emissions (Chen et al., 2016). The main industries in Chengdu including machinery, automobile, medicine, food, and information technology. With the rapid economic growth, the number of motor vehicles were 4.64 million (included 243,000 trucks) and the annual growth rate was N14% in Chengdu (Qiao et al., 2013). In addition, there are about 2600 urban construction sites (including housing, municipal and rail transit), and N800 of them in the central of city (Qiao et al., 2013), which have generated a lot of pollutant emissions. Chengdu is located in the central area of the Sichuan Basin, which is difficult to diffuse the urban atmospheric pollutants and prone to haze weather (Tao et al., 2013). Fang et al. (2016) showed that the annual average concentration of PM2.5 is 75–100 μg/m3 and about 3% mortality rate were associated with air particulate matter in Chengdu. Air pollution has become a public health concern in this city. Previous studies on heavy metals in dust from Chengdu were focused on the outdoor dust of content, particle size, pollution, source identification and health risk assessment (Chen et al., 2016; Qiao et al., 2013). However, there is few studies are related to the heavy metals in household dust from Chengdu. The major objectives of current study were as follows (1) to determine the heavy metals (Lead, Pb; Zinc, Zn; Copper, Cu; Chromium, Cr; Cadmium, Cd; Nickel, Ni) concentrations in household dust from Chengdu; (2) identify the correlations between heavy metals in household dust and the house attributes (such as resident habits, house age, paint and cooking frequency); and (3) to evaluate the human health risks (based on oral bioaccessibility) posed by heavy metal exposure through the three exposure ways of household dust. 2. Material and methods 2.1. Samples collection A total of 90 combined household dust samples (3 sub-samples were acquired randomly and combined with equal weight in each site) were collected in six urban districts in Chengdu from November 2014 to July 2015. There are geographic differences between samples. The household dust samples were obtained by a plastic brush and a dust collector from floor surfaces in all living areas and connecting rooms, avoiding potentially wet areas (kitchen and bathroom) to protect the integrity of the sample. Before each sampling, brushes, dustpans and dust collector were cleaned. These households were located in Wuhou (WH, n = 21), Chenghua (CH, n = 18), Jinniu (JN, n = 15), Jinjiang (JJ, n = 12), Gaoxin (GX, n = 12), and Qingyang (QY, n = 12). The dust samples were wrapped in aluminum foil, placed in zip-lock bags and transported to the laboratory. The samples were freeze-dried and homogenized by passing through a stainless steel 63 μm sieve. A questionnaire was designed for collect information from the resident volunteers to assess household attributes and resident personal habits. The data covered the following information: age of building, floor cover, smoking, open

Z. Cheng et al. / Science of the Total Environment 619–620 (2018) 621–629

windows time and frequency, number of occupants, floor level, sweeping frequency, air conditioning, wall cover, the time for last paint, cooking fuel, cooking frequency, and pet. Meanwhile, the general information of the volunteer was recorded, including body weight, gender, age, duration of stay in Chengdu, days/year of stay in Chengdu, and h/ day stay at home.

2.2. Analytical methods All the samples were digested by a MARS-6-CLASSIC model microwave digestion system (CEM, USA). Accurate amount of 0.5 g of dust sample was weighed and placed in high-pressure Teflon containers. Then, two drops of hydrogen peroxide solution and 10 ml of 65% nitric acid were added into digestion tubes (US EPA, 1996a, 1996b). After digestion, extracts were filtered through 5C Whatman filter paper, and diluted to a volume of 25 ml with Mili-Q water; then analyzed for Pb, Zn, Cu, Cr, Cd and Ni by inductively coupled plasma atomic emission spectrometer (ICP-OES, Perkin Elmer Optima 8300). Physiologically based extraction test (PBET) was employed to evaluate the oral bioaccessibility of heavy metals, simulating the chemical conditions of the gastro-intestinal tract. The step adopted in this study was based on Moreda-Piñeiro et al. (Moreda-Piñeiro et al., 2011) and our former study (Cheng et al., 2013) with minor changes. The whole digestion process is carried out in the dark. In brief, about 0.25 g of dust added to 50 ml polypropylene tubes with 30 ml gastric solution (2.0 g/l pepsin in 0.15 M NaCl, acidified with HCl to pH 1.8) and end to end shaken in the constant temperature oscillation (dark, 37 °C, 120 rpm, for 2 h), then centrifuged (3000 r/min, for 10 min) and filtrated with a 5C Whatman filter paper and a 0.45 μm syringe filter successively. The remaining materials in the reaction tubes were added with 30 ml intestinal juice (2.0 g/l pancreatin, 2.0 g/l amylase and 5 g/l bile salts, in 0.15 M NaCl, pH 6.8), and end to end shaken in the constant temperature oscillation (dark, 37 °C, 100 rpm, for 4 h), then after adding to a drop of concentrated hydrochloric acid (HCl, Guaranteed reagent) centrifuged (10,000 r/min, for 5 min) and filtrated with a 5C Whatman filter paper and a 0.45 μm syringe filter successively. All the extracting solutions were stored at 4 °C before instrumental analysis with ICP-OES (Perkin Elmer Optima 8300) for Pb, Zn, Cu, Cr, Cd and Ni. 2.3. QA/QC All of the samples were tested in triplicate. Three analytical blank, three standard reference materials (SRMs) and 10% replicate samples accompanied each sample batch (up to 40 samples). Three SRMs: NIST 2709a (San Joaquin Soil), NIST 1944 (New York/New Jersey Waterway Sediment) and NIST 2584 (indoor dust, NIST, USA). The recovery rates varied from 80.2% to 82.0% for Pb, from 83.0% to 84.2% for Zn, from 91.3% to 107% for Cu, from 83.9% to 87.9% for Cr, from 90.1% to 93.7% for Cd, and from 82.2% to 86.4% for Ni in household dust. The limits of quantification (LOQs) were calculated from the lowest concentration of the calibration curve. The LOQ of 6 heavy metals analyzed in samples was 0.1 mg·kg−1. Concentrations below the LOQ were assigned a value of 0.01× LOQ for statistical analysis.

2.4. Calculation of enrichment factor (EF) The crustal enrichment factor (EF) was utilized to differentiate an anthropogenic source from a natural origin, as well as to assess the degree of influence of human activity, which was calculated as Eq. (1) (Buat-Menard and Chesselet, 1979). In this study, manganese (Mn) was a conservative element, and was used as the reference element (Han et al., 2006). The background values of elements of soil in Chengdu, China were derived from China National Environmental Monitoring

623

Center (CNEMC, 1990), and were applied as reference concentrations.

 EF ¼ C n  ðsampleÞ=C ref  ðsampleÞ = Bn ðbaselineÞ=Bref  ðbaselineÞ

ð1Þ

where Cn (sample) is the concentration of the examined element in the household dusts; Cref (sample) is the concentration of the reference element (Mn) in the household dusts; Bn (baseline) is the background value of the examined element; and Bref (baseline) is the background value of the reference element (Mn). 2.5. Calculation of bioaccessibility The bioaccessibility (BA%) of each metals in household dust was calculated as the ratio of the concentration of the metals in stomach and intestinal phase to that in the total metal based on Eq. (2) (Kang et al., 2011). BA% ¼

CBA extracted Metal  100% Ctotal Metal

ð2Þ

2.6. Health risk assessment The exposure health influence of heavy metals in the household dust to the human body is used by the US Environmental Protection Agency (EPA) human health evaluation method (US EPA, 2001). There are three major exposure pathways for adults and children to heavy metals in household dust: (1) ingestion, (2) inhalation, and (3) dermal contact (Du et al., 2013; Wei and Yang, 2010). The dust and surface soils which b63 μm in particle size are easily resuspended into atmosphere, with the finer particles being capable of remaining airborne for considerable durations, and have a higher tendency to absorb by humans via the three exposure pathways than that in other particle size (Mohmand et al., 2015; Shilton et al., 2005; Zheng et al., 2010). Therefore, all the equations of the exposure estimates based on assumption that house dust has the same particle size distribution as soil. The average daily exposure dose (ADD, mg·kg−1·day−1) of heavy metals in household dust was calculated separately for three exposure pathways using Eqs. (6)–(8) (US EPA, 2002). And the average daily dose of the inhalation and dermal contact exposure pathways were calculated by total concentrations (acid digestion), the ingestion approach was calculated by oral bioaccessible concentrations (Wang et al., 2016). ADDing ¼ C  BA 

ADDinh ¼ C 

IngR  TEF  ED  10−6 BW  AT

InhR  TEF  ED PEF  BW  AT

ADDdermal ¼ C 

SL  SA  ABS  TEF  ED  10−6 BW  AT

ð6Þ

ð7Þ

ð8Þ

For three carcinogenic metals (Cr, Cd and Ni), the lifetime average daily doses (LADDs) were used to the assessment of cancer risk for three exposure routes and calculated as follow Eqs. (9)–(11) (US EPA, 1996a, 1996b; US EPA, 2002; Wang et al., 2016). LADDing ¼

LADDinh ¼

C  TEF  BA  AT  IngRchild  EDchild IngRadult  EDadult þ  10−6 ð9Þ  BWchild BWadult C  TEF AT PEF  InhRchild  EDchild InhRadult  EDadult þ  BWchild BWadult

ð10Þ

624

Z. Cheng et al. / Science of the Total Environment 619–620 (2018) 621–629

Table 1 The concentrations of heavy metals in household dust from Chengdu and other countries or cities. Concentrationa, mg·kg−1

Location

Chengdu, China Tokyo and Hiroshima, Japan Canada Birmingham, Plymouth, West Midlands and West Devon, United Kingdom Sydney, Australia Istanbul, Turkey Giza and Cairo, Egypt Guangzhou, China

Pb

Zn

Cu

Cr

Cd

Ni

123 57.9 210 181 76.2 28.1 222 699

675 920 833 666 372 832 114 344

161 304 279 339 93.3 156 192 68.4

82.7 67.8 117 n.a. 64.5 54.9 68.1 188

2.37 1.02 6.00 1.30 1.64 0.80 2.23 0.43

52.6 59.6 102 56.5 15.1 263 39.2 94.9

n

References

90 100 1025 32 82 31 16 10

This study (Yoshinaga et al., 2014) (Rasmussen et al., 2013) (Turner and Simmonds, 2006) (Chattopadhyay et al., 2003) (Kurt-Karakus, 2012) (Hassan, 2012) (Huang et al., 2014a, 2014b, 2014c)

n.a.: not reported. a Arithmetic mean.

LADDdermal ¼

C  TEF  ABS AT

  SLchild  SAchild  EDchild SLadult  SAadult  EDadult  þ  10−6 BWchild BWadult

ð11Þ C is the concentration of heavy metals in household dust, mg·kg−1; IngR is the ingestion rate, (children: 60 mg·day− 1; adults: 30 mg·day−1) (US EPA, 2011); InhR is the inhalation rate (children: 20 m3·day−1; adults: 7.6 m3·day−1) (US EPA, 2009); PEF is the particle emission factor (children and adults:1.36 × 109 m3·kg−1) (US EPA, 2002); SL is the skin adherence factor (children: 0.2 mg/cm2/day; adults: 0.07 mg/cm2/day) (US EPA, 2002); SA is the exposed skin area (children: 2800 cm2; adults: 5700 cm2) (US EPA, 2004); ABS is the dermal absorption factor (Only Cd, 0.001) (US EPA, 2004); TEF is the exposure frequency, represented by days/year of stay in Chengdu (children and adults: 300 days/year, from questionnaire); ED is the exposure duration, represented by years of stay in Chengdu (children: 6 years (US EPA, 2004); adults: 7 years, EDadult = duration in Chengdu (years) × (T/24)), and T is h/day stay at home, from questionnaire); BW is the body weight (children: 16 kg (Zhang et al., 2008); adults: 60 kg, from questionnaire); AT is the averaging time (for non-cancer, AT = ED × 365 (US EPA, 2004); for cancer, AT = 70 × 365 (Du et al., 2013)). The hazard quotient (HQ) is used for computing the non-carcinogenic impact of heavy metals in household dust. A hazard index (HI) is equal to the sum of HQ for numerous substances or numerous pathways (US EPA, 2009). Equally, the cancer risk (CR) is used to estimate that an individual exposure to carcinogenic hazards during a lifetime. Total cancer risk (TR) is the sum of CR for three pathways. The potential non-carcinogenic and carcinogenic risks for individual heavy metals could be acquired using the following equations (Hu et al., 2011; US EPA, 2007): HQ ¼ HI ¼

ADDing=inh=dermal RfD

X

HQi

CR ¼ LADDing=inh=dermal  SF TR ¼

X

CRi

ð12Þ ð13Þ ð14Þ ð15Þ

where RfD is the homologous reference dose, SF is the homologous slope factor. In this study, the values of RfD and SF for heavy metals were derived from regional screening levels (US EPA, 2012), except for Pb, which was obtained from the FAO/WHO (JECFA, 1993). The toxicity value of Cr(VI), much more toxic than Cr(III), was used to figure out the worst situation of Cr, and the SF and RfD of Cr(VI) were assumed as for total Cr (Huang et al., 2014b). All the SF and RfD values are tabulated in Table S1. An HQ or HI b 1 indicates that there is no significant risk of

non-carcinogenic effects, while HQ or HI N 1 indicates that there is occur a possibility of non-carcinogenic effects, with a probability which tends to increase as the value of HQ or HI increases (US EPA, 2001). For carcinogens, an CR or TR lower than 1 × 10−6 can be deemed to inappreciable, an CR or TR in the range of 1 × 10−6 to 1 × 10−4 can be regarded as acceptable or tolerable risk, and an CR or TR higher than 1 × 10−4 means that 1 in 10,000 people may develop any type of cancer from lifetime exposure to carcinogenic hazards (US EPA, 1989). 2.7. Statistical analysis SPSS 20.0 and Canoco 4.5 software packages were applied to perform the data of statistical analyses. Pearson's correlation coefficient analysis and Redundancy analysis (RDA) were used to analyze the relations between the heavy metals concentration and household environmental factors. Prior to RDA, the data was log-transformed to meet the normality assumptions. Cluster analysis (CA) and principal component analysis (PCA) identified the relationship among six metals in household dusts and their probable sources. In recent years, CA and PCA have also been widely used in dust metal studies (Han et al., 2006; Li et al., 2017; Shi et al., 2012). In this study, CA with Euclidean distance and Ward's method was performed. And PCA with the varimax rotation of Kaiser normalization was performed, to make the results more easily interpretable. The PCA loadings were plotted to inspect the similarities seen as clusters. 3. Results and discussion 3.1. Heavy metals in household dust The concentrations (mg·kg−1 dw) of heavy metals (Pb, Zn, Cu, Cr, Ni and Cd) on a dry weight basis in household dusts from Chengdu were showed in Table 1. Zinc showed the highest concentration (675 ± 377 mg·kg−1) in the household dust, followed by Cu (190 ± 321 mg·kg−1), Pb (123 ± 62.1 mg·kg−1), Cr (82.7 ± 30.6 mg·kg−1), Ni (52.6 ± 50.7 mg·kg−1) and Cd (2.37 ± 1.10 mg·kg−1), and the results was similar to previous studies on outdoor dust from Chengdu (Chen et al., 2016; Qiao et al., 2013). The median enrichment factor (EF) values of heavy metals in household dust were ranked in the order of Cd N Zn N Pb N Cu N Ni N Cr (Table 2). The median EF values of Cd (35.2), Zn (9.06) and Pb (5.09) were higher than 5, indicating the Table 2 The enrichment factors (EFs) of household dust in Chengdu (The EFs larger than 10 were marked in bold).

Background values (mg/kg) Min Max Median Average SD

Pb

Zn

Cu

Cr

Cd

Ni

28.9 0.62 10.7 5.09 5.03 2.53

82.1 1.84 25.8 9.06 9.69 5.42

29.7 0.93 17.9 4.74 6.40 4.09

73.7 0.60 3.08 1.26 1.32 0.49

0.08 8.55 84.6 35.2 37.2 17.2

31.1 0.40 10.9 1.65 1.99 1.92

Z. Cheng et al. / Science of the Total Environment 619–620 (2018) 621–629

household dust from Chengdu was significantly enriched (Loska et al., 1997). The median EF value of Cr (1.26) was close to 1, indicating that the source of Cr was mainly from the nature (Han et al., 2006). The median EF value of Cd (35.2) was much larger than 10, so it was consider to be derived from anthropogenic activities (Han et al., 2006). In Table 1, the concentrations of heavy metals in household dust from Chengdu may be low or moderate relative to the cities from Japan, UK, Australia, Turkey, Egypt and China, those areas may be highly polluted (expect Cd). Chengdu is the second largest automobile ownership (3.89 million) in China and the third largest automobile ownership in the world (China SignPost, 2013). In this study, the household dust samples were collected from the urban area of Chengdu with the heavy traffic, and the sampling houses were near to the street. The Pb may be attributed to huge vehicular traffic emissions (Amato et al., 2014). Although leaded petrol was prohibited in Chengdu since 2000, Pb deposited in the soil may enter urban dust by resuspension (Chen et al., 2014). The

625

Cu may be due to wear of engine parts and fuel and oil leakage (Charlesworth et al., 2003; Hassan, 2012; Yuen et al., 2012). Zinc is a common element in motor vehicles (including tires, vehicle brake linings, metallic parts) and galvanized road equipments, so the tyre abrasion, brake wear, corrosion of automobile parts and road equipments could be the important source of Zn in household dust of city (Al-Rajhi et al., 1996; López et al., 2011; Yuen et al., 2012). The Ni could be from Ni plating and alloys in cars and yellow paint on roads (Chandra Mouli et al., 2006; Madany et al., 1994). The source of Ni may also be associated with burning of mosquito coils and stainless steel debris (Lin and Shen, 2005; Yoshinaga et al., 2014). However, the Cd concentrations (2.37 ± 1.10 mg·kg−1) was higher than that reported in Guangzhou (China), Istanbul (Turkey), Tokyo and Hirosbima (Japan) (Huang et al., 2014c; Kurt-Karakus, 2012; Yoshinaga et al., 2014), the similar results were found in previous study about outdoor dust from Chengdu (Li et al., 2017). Previous studies reported the

Fig. 1. House factors based on questionnaire results in Chengdu households.

626

Z. Cheng et al. / Science of the Total Environment 619–620 (2018) 621–629

concentrations of Cd in household dusts might be partly arise from outdoor which due to erosion and wear of building materials, tires, Cd-batteries and fertilizer application (Saeedi et al., 2012; Wei et al., 2010; Yildirim and Tokalioğlu, 2016). In addition, the heavy metals of household dust samples from Chengdu showed higher concentrations than that in the street dust from Chengdu (Pb, 82.3, mg·kg− 1; Cu, 100 mg·kg− 1; Ni, 24.4 mg·kg− 1; Zn, 296 mg·kg−1; Cr, 84.3 mg·kg−1), except for Cr (1.66 mg·kg−1) (Li et al., 2017), that was similar to previous studies (Glorennec et al., 2012; Huang et al., 2014c; Jaradat et al., 2004), so heavy metals in household dust should have other contributors. 3.2. Redundancy analysis and principal component analysis The information gathered on household factors based on questionnaires showed that 100% of the urban residents opened their houses windows every day, 50.0% of the dwelling units were in 1 to 5 layers, 70.8% of the houses has 1 to 3 people, and 25.0% of the houses had pet (Fig. 1). Previous studies reported that cooking and smoking may be other contributors to heavy metals in urban household environment (Kim and Fergusson, 1993; Kurt-Karakus, 2012; Rasmussen et al., 2013). The percentage of fuel types used for cooking was 62.5%, 12.5%, 12.5%, 4.17% and 8.33% for natural gas, electricity, natural gas and electricity, coal gas and all, respectively in Chengdu. Moreover, 37.5% of the houses had frying as a method of cooking (twice/day) and 70.8% of the houses had smokers. The survey results also showed 4.17% of the houses had carpet, 75.0% of houses were white latex paint, 12.5% of the house walls had used plastic wallpaper, and the time for last pain of 54.2% houses and the age of 83.3% houses were N5 years. In addition, 75.0% of the houses had air condition, 12.2% and 41.7% of the dwelling units had their floors swept every day and 2 to 3 times a week, respectively. The RDA was applied to elucidate the relations between heavy metals concentrations and household factors. Fig. 2 revealed that the RDA1 and RDA2 explained 34.9% and 7.20% of the total variability in

heavy metals, respectively. The results of RDA showed that the smoking was the important factor of heavy metals enriched in household dust, especially for Pb, Zn and Cd, and the Spearman's correlation coefficient for smoking- Pb, smoking- Zn and smoking- Cd was 0.470 (p b 0.05), 0.550 (p b 0.01) and 0.419 (p b 0.05), respectively (Table 3). The results could be explained by the amount of heavy metals in cigarette. (Bohlandt et al., 2012; Rasmussen et al., 2013). Pourkhabbaz and Pourkhabbaz (2012) observed that the concentrations of Cd, Cu, Ni, Zn and Pb in cigarette were respectively 2.71 mg·kg− 1, 9.70 mg·kg−1, 17.9 mg·kg−1, 27.0 mg·kg−1 and 2.07 mg·kg−1. The heavy metals in cigarettes can be released into the indoor environment by suspended particulate matter and soot generated from cigarette smoking, so the cigarette smoking is one of the most important sources for the heavy metals in household dust (Bohlandt et al., 2012). In this study, 70.8% of the houses had smokers (Fig. 1). The wall cover may have the more important effects on the concentrations of metals in the household dust (Fig. 2), and the Spearman's correlation analysis showed that Zn-wall cover, Pb -wall cover and Cu -wall cover were significant correlation (p b 0.05) (Table 3). In this study, 75.0% of houses are white latex paint (Fig. 1) which widely use lithopone (66% BaSO4/34% ZnSO4) and lead carbonate (PbCO3) as filler (Jaradat et al., 2004). As well as there are some Zn2+ and Cu2+ in the antibacterial fungicide of latex paint. In this study, the age of 83.3% houses were N 6 years, and the last pain time of 54.2% houses were N 5 years (Fig. 1). Furthermore, all the heavy metals displayed an increased trend in the metals concentration with the time for last paint and age of building (Fig. 2), and the Spearman's correlation coefficient for Znthe time for last paint and age of building were 0.652 (p b 0.01) and 0.408 (p b 0.05), respectively (Table 3), which could be due to the flaking of paint off the wall. The Cd-the time for last paint also was significant positive correlation (p b 0.05) (Table 3). The survey results showed 12.5% of the house had used plastic wallpaper (Fig. 1), and the Cd was added as catalyst, stabilizer or colorant to interior plastic building materials and plastic components (Duarte et al., 2010; Massos and Turner, 2017), so the old plastic products in house are potential source of Cd in household dust. In addition, the older houses usually have worn and deformed windows and doors, and crevices in floors, which may cause heavy metals to accumulate in household dust (Rasmussen et al., 2013; Tong and Lam, 2000). There was no significant correlation between heavy metals and cooking fuel or cooking frequency (p N 0.05) (Table 3), but previous study found that cooking was a contributor to PAHs in urban household dust (Wang et al., 2013), that showed the household cooking was one of indoor pollution source. In Table 3, heavy metals-sweeping frequency was negative correlation (p N 0.05), that indicated the heavy metals in household had a downward trend with cleaning. Sweeping frequency may be another factor that directly affects metal levels in the household dust (Tong and Lam, 2000).

Table 3 The bivariate correlation analysis of heavy metals in household dust and the household factors.

Fig. 2. Redundancy analysis (RDA) of the relationship between the household environmental factors and heavy metals in household dust. Note: The arrow with blue and small represent the heavy metals, the red and big arrow means the household environmental factors, the length of arrow means the influence of the factor. The cosine of the angle between the arrows of the environmental factors and the arrows of the heavy metals represents the correlation between heavy metals and household environmental factors. The dotted line means the suppositional axis of the RDA result. A is floor level, B is age of building, C is floor cover, D is smoking allowed, E is number of occupants, F is sweeping frequency, G is air condition, H is wall cover, I is the time for last paint, J is cooking fuel, K is cooking frequency, L is pet. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Floor level Age of building Floor cover Smoking Number of occupants Sweeping frequency Air condition Wall cover The time for last paint Cooking fuel Cooking frequency Pet

Pb

Zn

Cu

−0.341 0.330 0.l84 0.470⁎ 0.207 −0.221 0.236 0.497⁎

−0.276 0.408⁎ 0.134 0.550⁎⁎ 0.014 −0.006 0.000 0.512⁎ 0.652⁎⁎

−0.270 0.020 0.028 0.232 0.161 −0.070 −0.118 0.417⁎

Cr

−0.278 0.227 0.150 0.179 0.314 −0.070 0.167 0.107 0.132 0.200 0.305 −0.010 0.066 −0.018 0.174 −0.187 −0.131 0.007 0.195 0.083 0.222 0.139 0.083

⁎ Correlation is significant at the 0.05 level (2-tailed). ⁎⁎ Correlation is significant at the 0.01 level (2-tailed).

Cd

Ni

−0.238 0.083 −0.100 0.419⁎ 0.080 −0.059 0.083 0.254 0.459⁎ 0.140 0.050 0.083

−0.446⁎ 0.275 0.114 0.338 0.015 −0.150 0.334 0.102 0.353 −0.261 0.046 0.153

Z. Cheng et al. / Science of the Total Environment 619–620 (2018) 621–629

There was a negative correlation between the heavy metals concentrations and floor levels (Fig. 2, Table 3), but only Ni-floor level was significant negative correlation (p b 0.05) (Table 3). The concentrations of heavy metals in household dust were inversely proportional to the height of the floor. The result is contrary to previous study in coastal city which was no variation in the contents of heavy metals in household dust among different floor levels, and that may be ascribed to the strong monsoon winds and oceanic effects contributed to atmospheric turbulence in Hong Kong (Tong and Lam, 2000). However, due to the unique climate of the Sichuan basin, most wind direction in Chengdu are the calm and the frequency of calm is up to 43.0% (Chengdu Government, 2017), so the diffusion of airborne dust satisfied a straight altitude decay function from the road level (Strbova et al., 2017). In the general rule for architectural design of civil buildings in China, the essential requirement of constructions in the northern is to prevent freezing and cold, but in the southern that is to release heat and avoid moisture (Ministry of Construction of the People's Republc of China, 2005), therefore, the civils building in the southern was worse air tightness and more focus on indoor and outdoor ventilation than that in the northern (Chen et al., 2012; Ji and Duanmu, 2017). Chengdu is located in southwestern China, and the survey results showed that 100% of the urban residents opened their houses windows every day and 50.0% of the dwelling units were in 1 to 5 layers (Fig. 1), indicated that metals bearing household dust were partly originated from the outside suspended particulates, such as street dust and construction dust (Chen et al., 2016; Qiao et al., 2013). In addition, the decrease in metals in household dust with height of floor indicate that most particulates are too large to be easily resuspended indoors. Therefore, these particulates are tracked in from shoes, animals, etc. more than being transported from outdoor air, and the number of residents and pets in house could also affect to the concentrations of heavy metals in household dust (Kurt-Karakus, 2012). 3.3. Probable source identification The PCA was performed for all household dust samples to determine the relationships among six heavy metals, and the result showed the first three factors (1, 37.1%; 2, 26.2%; 3, 18.4%) accounting for 81.7% of the total variance (Fig. 3). Factor 1 was heavily weighted by Zn, Cd and Ni; Factor 2 was dominated by Pb and Cu; Factor 3 was dominated by Cr. The CA analysis results for the metals studied were consistent with the PCA analysis, Fig. S1 displayed three clusters: (A) Zn-Cd-Ni,

Fig. 3. PCA results in three-dimensional space: plot of the first three principal components loading.

627

(B) Pb-Cu, (C) Cr. Besides, Pearson's correlation coefficients among the six metals indicated that Zn, Cd and Ni had significantly positive correlation (p b 0.01) (Table S2). According to the statistical results and EF values can identify the probable emission origins. The heavy metals profile of factor 1 was consistent with the emission characteristic of the Cd, Zn, and Ni composition from erosion and wear of tires and alloy, corrosion of automobile parts, municipal road facilities, and indoor smoking (Chandra Mouli et al., 2006; Pourkhabbaz and Pourkhabbaz, 2012; Yuen et al., 2012). Previous studies have suggested that the Pb in urban dust may be mainly from vehicle exhausts emissions, even though the leaded petrol was prohibited more than twenty years (Amato et al., 2014; Chen et al., 2014). Potential vehicular sources of Cu in this study included fuel and oil leakage (Hassan, 2012). Wall paint may also lead to the accumulation of Pb and Cu (Chattopadhyay et al., 2003; Tong and Lam, 2000). Thus, the factor 2 appeared to partly derive from traffic sources, and partly stem from the latex paint additives. The PCA and CA analysis showed Cr was an independent cluster and no correlation to other metals. And the median EF value (1.26) for Cr was close to 1, which point to the natural source (Han et al., 2006). Therefore, Cr emission source was mainly from the natural source.

3.4. Health risk assessment The PBET results can show the quantity of contaminants which can be dissolved from the ingested dust in the intestines and stomach (Cao et al., 2009; Hu et al., 2011). The mean bioaccessibility of Cd (80.2%), Zn (70.0%), Pb (43.9%), Cu (39.7%), Ni (30.5%) and Cr (8.57%) for heavy metals in household dust. The result was similar to previous studies, which the bioavailability among the studied heavy metals was great differences, and that could be explained by the different forms may occur with these metals in the digested system. (Morman et al., 2009; Wang et al., 2016). The assessment results of non-carcinogenic health risk due to heavy metals exposures via different routes in the household dust are showed in Fig. S2. The three exposure routes of heavy metals (except for Cr and Cd) for children and adults declined in the following order: ingestion, dermal contact and inhalation, suggesting that ingestion of household dust appears to be the important exposure pathway to harm human health. Previously studies also identified oral ingestion as the major exposure route to dust particles for humans (Huang et al., 2014a; Wang et al., 2014), that could be explained by the larger size particles are not easily resuspended indoors, and heavy metals via household dust exposure to residents is likely to be more dependent on hand to mouth contact (particularly by young children) than on inhalation and dermal contact. Therefore, particle size of household dust may be an important factor on the contribution of the exposure routes. Moreover, the contributions of HQing to HI for children were higher than those for adults (Fig. S3). The result may be partly attributable to particular behavioral pattern of the children, such as frequent pica behavior and hand or finger sucking (Li et al., 2015; Wei et al., 2015). However, the HQs of Cr and Cd for dermal contact were higher than ingestion and inhalation. All HI values for both children and adults were lower than the safe level of 1 (Fig. S3), suggesting that there were no significant non-carcinogenic risks from exposure to heavy metals in household dust. The HI values for adults were approximately an order of magnitude lower than that for children, so the children could have more potential health risks from exposure to heavy metals in household dusts from Chengdu. For carcinogenic effects (Fig. S4), Cd was calculated by the ingestion, inhalation and dermal exposure modes, while Cr and Ni was only assessed through inhalation exposure modes, because there was short of SF for the ingestion and dermal exposure routes. The carcinogenic risks were all lower than 1 × 10−4, indicating that the total cancer risk for Cd, Cr and Ni can be acceptable in Chengdu. However, the old residential buildings, lower residential layer (1 to 5 floor) and smoking habit may be more

628

Z. Cheng et al. / Science of the Total Environment 619–620 (2018) 621–629

potential health risks exposure to heavy metals via household dust should not be overlooked. 4. Conclusions The present study investigated the concentrations of Pb, Zn, Cu, Cr, Cd and Ni in household dust from Chengdu. Principal component analysis and redundancy analysis showed heavy metals in household dust were partly originated from corrosion of alloys, old building materials and paint. In addition, the metals in household dust were affected by indoor smoking and lower residential layer. There were no non-carcinogenic and carcinogenic risks from the heavy metals in household dust for the residents in Chengdu. The finer particles in air (e.g. PM10 and PM2.5) are more easily adsorbed the heavy metal than other particle size, therefore, further work is recommended to investigate concentrations of heavy metals in PM10 and PM2.5 of various indoor environments in Chengdu and assess their health risk. Acknowledgments Financial support from National Natural Science Foundation of China (No. 21507095), the Sichuan province project Education Fund (No. 16ZA0036), The Sichuan Provincial Youth Science and Technology Fund (No. 2017JQ0035). Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi. org/10.1016/j.scitotenv.2017.11.144. References Akinwunmi, F., Akinhanmi, T.F., Atobatele, Z.A., Adewole, O., Odekunle, K., Arogundade, L.A., et al., 2017. Heavy metal burdens of public primary school children related to playground soils and classroom dusts in Ibadan North-West local government area, Nigeria. Environ. Toxicol. Pharmacol. 49, 21–26. Al-Rajhi, M.A., Seaward, M.R.D., Al-Aamer, A.S., 1996. Metal levels in indoor and outdoor dust in Riyadh, Saudi Arabia. Environ. Int. 22, 315–324. Amato, F., Cassee, F.R., van der Gon HA, Denier, Gehrig, R., Gustafsson, M., Hafner, W., 2014. Urban air quality: the challenge of traffic non-exhaust emissions. J. Hazard. Mater. 275, 31–36. Bohlandt, A., Schierl, R., Diemer, J., Koch, C., Bolte, G., Kiranoglu, M., et al., 2012. High concentrations of cadmium, cerium and lanthanum in indoor air due to environmental tobacco smoke. Sci. Total Environ. 414, 738–741. Buat-Menard, P., Chesselet, R., 1979. Variable influence of the atmospheric flux on the trace metal chemistry of oceanic suspended matter. Earth Planet. Sci. Lett. 42, 399–411. Butte, W., Heinzow, B., 2002. Pollutants in house dust as indicators of indoor contamination. Rev. Environ. Contam. Toxicol. 175, 1–46. Cao, X., Wahbi, A., Ma, L., Li, B., Yang, Y., 2009. Immobilization of Zn, Cu, and Pb in contaminated soils using phosphate rock and phosphoric acid. J. Hazard. Mater. 164, 555–564. Chandra Mouli, P., Venkata Mohan, S., Balaram, V., Praveen Kumar, M., Jayarama Reddy, S., 2006. A study on trace elemental composition of atmospheric aerosols at a semi-arid urban site using ICP-MS technique. Atmos. Environ. 40, 136–146. Charlesworth, S., Everett, M., Mccarthy, R., Ordóñez, A., De, M.E., 2003. A comparative study of heavy metal concentration and distribution in deposited street dusts in a large and a small urban area: Birmingham and Coventry, West Midlands, UK. Environ. Int. 29, 563–573. Chattopadhyay, G., Lin, C.P., Feitz, A.J., 2003. Household dust metal levels in the Sydney metropolitan area. Environ. Res. 93, 301–307. Chen, S.Q., Levine, M.D., Li, H.Y., Yowargana, P., Xie, L.N., 2012. Measured air tightness performance of residential buildings in North China and its influence on district space heating energy use. Energ. Buildings 51, 157–164. Chen, H., XW, Lu, Li, L.Y., Gao, T.N., Chang, Y.Y., 2014. Metal contamination in campus dust of Xi'an, China: a study based on multivariate statistics and spatial distribution. Sci. Total Environ. 484, 27–35. Chen, M., Pi, L., Luo, Y., Geng, M., Hu, W., Li, Z., et al., 2016. Grain size distribution and health risk assessment of metals in outdoor dust in Chengdu, southwestern China. Arch. Environ. Contam. Toxicol. 70, 534–543. Cheng, Z., Nie, X.P., Wang, H.S., Wong, M.H., 2013. Risk assessments of human exposure to bioaccessible phthalate esters through market fish consumption. Environ. Int. 57-58, 75–80. Chengdu Government, 2017. Chengdu Municipal People's Government Network, Climatic Conditions. (http://www.chengdu.gov.cn/servicelist/cdgk05/ In Chinese [Accessed 27 June 2017]).

China SignPost, 2013. Counting Car: rising private automobile ownership in chinese cities paves road for gasoline demand. http://www.chinasignpost.com/2013/06/23/ counting-cars-rising-private-automobile-ownership-in-chinese-cities-paves-roadfor-gasoline-demand/, Accessed date: 27 June 2017. CNEMC, 1990. Soil Element Background Value in China Beijing. China Environmental Science Press (In Chinese). Du, Y.R., Gao, B., Zhou, H.D., XX, Ju, Hao, H., Yin, S.H., 2013. Health risk assessment of heavy metals in road dusts in urban parks of Beijing, China. Procedia Environ Sci 18, 299–309. Duarte, A.T., Dessuy, M.B., Silva, M.M., Vale, M.G.R., Welz, B., 2010. Determination of cadmium and lead in plastic material from waste electronic equipment using solid sampling graphite furnace atomic absorption spectrometry. Microchem. J. 96, 102–107. Fang, D., Qg, Wang, Li, H., Yu, Y., Lu, Y., Qian, X., 2016. Mortality effects assessment of ambient PM2.5 pollution in the 74 leading cities of China. Sci. Total Environ. 569–570, 1545–1552. Glorennec, P., Lucas, J.P., Mandin, C., Le Bot, B., 2012. French children's exposure to metals via ingestion of indoor dust, outdoor playground dust and soil: contamination data. Environ. Int. 45, 129–134. Han, Y.M., PX, Du, Cao, J.J., Posmentier, E.S., 2006. Multivariate analysis of heavy metal contamination in urban dusts of Xi'an, Central China. Sci. Total Environ. 355, 176–186. Hassan, S.K.M., 2000. A Study on Indoor Air Quality in Greater Cairo. Faculty of Science, Cairo University, M.Sc (Thesis). Hassan, S.K.M., 2012. Metal concentrations and distribution in the household, stairs and entryway dust of some Egyptian homes. Atmos. Environ. 54, 207–215. He, C.T., Zheng, X.B., Yan, X., Zheng, J., Wang, M.H., Tan, X., et al., 2017. Organic contaminants and heavy metals in indoor dust from e-waste recycling, rural, and urban areas in South China: spatial characteristics and implications for human exposure. Ecotoxicol. Environ. Saf. 140, 109–115. Hogervorst, J., Plusquin, M., Vangronsveld, J., Nawrot, T., Cuypers, A., Van Hecke, E., et al., 2007. House dust as possible route of environmental exposure to cadmium and lead in the adult general population. Environ. Res. 103, 30–37. Hu, X., Zhang, Y., Luo, J., Wang, T., Lian, H., Ding, Z., 2011. Bioaccessibility and health risk of arsenic, mercury and other metals in urban street dusts from a mega-city, Nanjing, China. Environ. Pollut. 159, 1215–1221. Huang, M., Chen, X., Shao, D., Zhao, Y., Wang, W., Wong, M.H., 2014a. Risk assessment of arsenic and other metals via atmospheric particles, and effects of atmospheric exposure and other demographic factors on their accumulations in human scalp hair in urban area of Guangzhou, China. Ecotoxicol. Environ. Saf. 102, 84–92. Huang, M., Chen, X., Zhao, Y., Yu Chan, C., Wang, W., Wang, X., et al., 2014b. Arsenic speciation in total contents and bioaccessible fractions in atmospheric particles related to human intakes. Environ Pollut 188, 37–44. Huang, M.J., Wang, W., Chan, C.Y., Cheung, K.C., Man, Y.B., Wang, X., et al., 2014c. Contamination and risk assessment (based on bioaccessibility via ingestion and inhalation) of metal(loid)s in outdoor and indoor particles from urban centers of Guangzhou, China. Sci. Total Environ. 479–480, 117–124. Hunt, A., Johnson, D.L., Griffith, D.A., 2006. Mass transfer of soil indoors by track-in on footwear. Sci. Total Environ. 370, 360–371. Jaradat, Q.M., Momani, K.A., Jbarah, A.A., Massadeh, A., 2004. Inorganic analysis of dust fall and office dust in an industrial area of Jordan. Environ. Res. 96, 139–144. JECFA, 1993. Evaulation of certain food additives and contaminants: 41st report of the Joint FA/WHO expert committe on food additives. Technical Reports Series, No.837. World Health Organization, Geneva. Ji, Y.M., Duanmu, L., 2017. Airtightness field tests of residential buildings in Dalian, China. Build. Environ. 119, 20–30. Kang, Y., Cheung, K.C., Wong, M.H., 2011. Mutagenicity, genotoxicity and carcinogenic risk assessment of indoor dust from three major cities around the Pearl River Delta. Environ. Int. 37, 637–643. Kim, N., Fergusson, J., 1993. Concentrations and sources of cadmium, copper, lead and zinc in house dust in Christchurch, New Zealand. Sci. Total Environ. 138, 1–21. Kurt-Karakus, P.B., 2012. Determination of heavy metals in indoor dust from Istanbul, Turkey: estimation of the health risk. Environ. Int. 50, 47–55. Li, H.B., Cui, X.Y., Li, K., Li, J., Juhasz, A.L., Ma, L.Q., 2014. Assessment of in vitro lead bioaccessibility in house dust and its relationship to in vivo lead relative bioavailability. Environ. Sci. Technol. 48, 8548–8555. Li, K.X., Liang, T., Wang, L.Q., Yang, Z.P., 2015. Contamination and health risk assessment of heavy metals in road dust in Bayan Obo Mining Region in Inner Mongolia, North China. J. Geogr. Sci. 25, 1439–1451. Li, H.H., Chen, L.J., Yu, L., Guo, Z.B., Shan, C.Q., Lin, J.Q., et al., 2017. Pollution characteristics and risk assessment of human exposure to oral bioaccessibility of heavy metals via urban street dusts from different functional areas in Chengdu, China. Sci. Total Environ. 586, 1076–1084. Lin, T.S., Shen, F.M., 2005. Trace metals in mosquito coil smoke. Bull. Environ. Contam. Toxicol. 74, 184–189. López, M.L., Ceppi, S., Palancar, G.G., Olcese, L.E., Tirao, G., Toselli, B.M., 2011. Elemental concentration and source identification of PM10 and PM2.5 by SR-XRF in Córdoba City, Argentina. Atmos. Environ. 45, 5450–5457. Loska, K., Cebula, J., PelczaR, J., Wiechula, D., Kwapulinski, J., 1997. Use of enrichment, and contamination factors together with geoaccumulation indexes to evaluate the content of Cd, Cu, and Ni in the Rybnik water reservoir in Poland. Water Air Soil Pollut. 347–365. Madany, I.M., Akhter, M.S., Jowder, O.A.A., 1994. The correlations between heavy metals in residential indoor dust and outdoor street dust in Bahrain. Environ. Int. 20, 483–492. Maertens, R.M., Bailey, J., White, P.A., 2004. The mutagenic hazards of settled house dust: a review. Mutat. Res. 567, 401–425.

Z. Cheng et al. / Science of the Total Environment 619–620 (2018) 621–629 Marcotte, S., Estel, L., Minchin, S., Leboucher, S., Le Meur, S., 2017. Monitoring of lead, arsenic and mercury in the indoor air and settled dust in the Natural History Museum of Rouen (France). Atmos. Pollut. Res. 8, 483–489. Massos, A., Turner, A., 2017. Cadmium, lead and bromine in beached microplastics. Environ. Pollut. 227, 139–145. Ministry of Construction of the People's Republc of China, 2005. General Rule for Architectural Design of Civil Buildings, GB50352-2005. (In Chinese). Mohmand, J., Eqani, S.A., Fasola, M., Alamdar, A., Mustafa, I., Ali, N., et al., 2015. Human exposure to toxic metals via contaminated dust: bio-accumulation trends and their potential risk estimation. Chemosphere 132, 142–151. Moreda-Piñeiro, J., Moreda-Piñeiro, A., Romarís-Hortas, V., Moscoso-Pérez, C., LópezMahía, P., Muniategui-Lorenzo, S., et al., 2011. In-vivo and in-vitro testing to assess the bioaccessibility and the bioavailability of arsenic, selenium and mercury species in food samples. Trends Anal. Chem. 30, 324–345. Morman, S.A., Plumlee, G.S., Smith, D.B., 2009. Application of in vitro extraction studies to evaluate element bioaccessibility in soils from a transect across the United States and Canada. Appl. Geochem. 24, 1454–1463. Needleman, H., 2009. Low level lead exposure: history and discovery. Ann. Epidemiol. 19, 235–238. Nriagu, J.O., 1988. A silent epidemic of environmental metal poisoning? Environ. Pollut. 50, 139–161. Olujimi, O., Steiner, O., Goessler, W., 2015. Pollution indexing and health risk assessments of trace elements in indoor dusts from classrooms, living rooms and offices in Ogun State, Nigeria. J. Afr. Earth Sci. 101, 396–404. Pourkhabbaz, A., Pourkhabbaz, H., 2012. Investigation of toxic metals in the tobacco of different iranian cigarette brands and related health issues. Iran J. Basic Med. Sci. 15, 636–644. Qiao, X., Schmidt, A.H., Tang, Y., YH, Xu, Zhang, C.S., 2013. Demonstrating urban pollution using toxic metals of road dust and roadside soil in Chengdu, southwestern China. Stoch. Env. Res. Risk A. 28, 911–919. Rasmussen, P.E., 2004. Can metal concentrations in indoor dust be predicted from soil geochemistry? J. Anal. Sci. Spectrosc. 49, 166–174. Rasmussen, P.E., Levesque, C., Chenier, M., Gardner, H.D., Jones-Otazo, H., Petrovic, S., 2013. Canadian house dust study: population-based concentrations, loads and loading rates of arsenic, cadmium, chromium, copper, nickel, lead, and zinc inside urban homes. Sci. Total Environ. 443, 520–529. Saeedi, M., Li, L.Y., Salmanzadeh, M., 2012. Heavy metals and polycyclic aromatic hydrocarbons: pollution and ecological risk assessment in street dust of Tehran. J. Hazard. Mater. 227-228, 9–17. Shi, X., Chen, L., Wang, J., 2012. Multivariate analysis of heavy metal pollution in street dusts of Xianyang city, NW China. Environ. Earth Sci. 69, 1973–1979. Shilton, V.F., Booth, C.A., Smith, J.P., Giess, P., Mitchell, D.J., Williams, C.D., 2005. Magnetic properties of urban street dust and their relationship with organic matter content in the West Midlands, UK. Atmos. Environ. 39, 3651–3659. Štrbová, K., Raclavská, H., Bílek, J., 2017. Impact of fugitive sources and meteorological parameters on vertical distribution of particulate matter over the industrial agglomeration. Journal of Environmental Management 203, 1190–1198. Tao, J., Zhang, L.M., Engling, G., Zhang, R.J., Yang, Y.H., Cao, J.J., et al., 2013. Chemical composition of PM2.5 in an urban environment in Chengdu, China: importance of springtime dust storms and biomass burning. Atmos. Res. 122, 270–283. Thatcher, T.L., Layton, D.W., 1995. Deposition, resuspension, and penetration of particles within a residence. Atmos. Environ. 29, 1487–1497. Thomas, L.D., Hodgson, S., Nieuwenhuijsen, M., Jarup, L., 2009. Early kidney damage in a population exposed to cadmium and other heavy metals. Environ. Health Perspect. 117, 181–184. Tong, S.T.Y., Lam, K.C., 2000. Home sweet home? A case study of household dust contamination in Hong Kong. Sci. Total Environ. 256, 115–123. Turner, A., Hefzi, B., 2010. Levels and bioaccessibilities of metals in dusts from an arid environment. Water Air Soil Pollut. 210, 483–491. Turner, A., Ip, K.H., 2007. Bioaccessibility of metals in dust from the indoor environment: application of a physiologically based extraction test. Environ. Sci. Technol. 41, 7851–7856.

629

Turner, A., Simmonds, L., 2006. Elemental concentrations and metal bioaccessibility in UK household dust. Sci. Total Environ. 371, 74–81. US EPA, 1989. Risk assessment guidance for superfund. Human Health Evaluation Manual. Office of Soild Waste and Emergency Response. vol. 1. US EPA, 1996a. Soil screening guidance: technical background document. Office of Soild Waste and Emergency Response. US EPA, 1996b. Method 3052: Microwave Assisted Acid Digestion of Siliceous and Organically Based Matrices SW-846. (Wachington, DC). US EPA, 1997. Exposure factors handbook. National Center for Environmental Assessment. Office of Research and Development, Washington, D.C. US EPA, 2001. Risk Assessment Guidance for Superfund: Volume III-Part A, Process for Conducting Probabilistic Risk Assessment Office of Emergency and Remedial Response. U.S. Environmental Protection Agency, Washington, D.C. US EPA, 2002. Supplemental Guidance for Developing Soil Screening Levels for Superfund Sites. Environmental Protection Agency, Washington, DC. US EPA, 2004. Risk Assessment Guidance for Superfund Volume I: Human Health Evaluation Manual (Part E, Supplemental Guidance for Dermal Risk Assessment). Office of Superfund Remediation and Technology Innovation, Washington, D.C. US EPA, 2007. Estimation of Relative Bioavailablity of Lead in Soil and Soil-like Materials Using In Vivo and In Vitro Methods. OSWER 9285.7–77. Office of Solid Waste and Emergency Response, U.S. Environmental Protection Agency, Washington, DC. US EPA, 2009. Risk Assessment Guidance for Superfund Volume I: Human Health Evaluation Manual. Office of Superfund Remediation and Technology Innovation, Washington, D.C. US EPA, 2011. Exposure factors handbook. National Center for Environmental Assessment. Office of Research and Development, Washington, D.C. US EPA, 2012. Regional Screening Level (RSL) Summery Table. http://www.epa.gov/ reg3hwmd/risk/human/rb-concentration_table/Generic_Tables/index.htm, Accessed date: 6 March 2017. Wang, W., Wu, F., Zheng, J., Wong, M.H., 2013. Risk assessments of PAHs and Hg exposure via settled house dust and street dust, linking with their correlations in human hair. J. Hazard. Mater. 263 (Pt 2), 627–637. Wang, W., Zheng, J., Chan, C.-Y., Huang, M.-j., Cheung, K.C., Wong, M.H., 2014. Health risk assessment of exposure to polybrominated diphenyl ethers (PBDEs) contained in residential air particulate and dust in Guangzhou and Hong Kong. Atmos. Environ. 89, 786–796. Wang, J.H., Li, S.W., Cui, X.Y., Li, H.M., Qian, X., Wang, C., et al., 2016. Bioaccessibility, sources and health risk assessment of trace metals in urban park dust in Nanjing, Southeast China. Ecotoxicol. Environ. Saf. 128, 161–170. Wei, B.G., Yang, L.S., 2010. A review of heavy metal contaminations in urban soils, urban road dusts and agricultural soils from China. Microchem. J. 94, 99–107. Wei, B.G., Jiang, F.Q., Li, X.M., Mu, S.Y., 2010. Heavy metal induced ecological risk in the city of Urumqi, NW China. Environ. Monit. Assess. 160, 33. Wei, X., Gao, B., Wang, P., Zhou, H., Lu, J., 2015. Pollution characteristics and health risk assessment of heavy metals in street dusts from different functional areas in Beijing, China. Ecotoxicol. Environ. Saf. 112, 186–192. Yildirim, G., Tokalioğlu, Ş., 2016. Heavy metal speciation in various grain sizes of industrially contaminated street dust using multivariate statistical analysis. Ecotoxicol. Environ. Saf. 128, 369–376. Yoshinaga, J., Yamasaki, K., Yonemura, A., Ishibashi, Y., Kaido, T., Mizuno, K., et al., 2014. Lead and other elements in house dust of Japanese residences–source of lead and health risks due to metal exposure. Environ. Pollut. 189, 223–228. Yuen, J.Q., Olin, P.H., Lim, H.S., Benner, S.G., Sutherland, R.A., Ziegler, A.D., 2012. Accumulation of potentially toxic elements in road deposited sediments in residential and light industrial neighborhoods of Singapore. J. Environ. Manag. 101, 151–163. Zhang, S.Y., Han, Y.S., Shen, X.Z., Ma, Z.G., Liu, G., Liu, L.G., 2008. Growthcharts of height, weight and body mass index for Han Chinese children and adolescent from large and middling cities of China. Chin. J. Child Health Care 16, 257–259. Zheng, N., Liu, J., Wang, Q., Liang, Z., 2010. Health risk assessment of heavy metal exposure to street dust in the zinc smelting district, Northeast of China. Sci. Total Environ. 408, 726–733.