Science of the Total Environment 526 (2015) 262–270

Contents lists available at ScienceDirect

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

Metal concentrations and distribution in paint waste generated during bridge rehabilitation in New York State Zhan Shu a, Lisa Axe a,⁎, Kauser Jahan b, Kandalam V. Ramanujachary c, Carl Kochersberger d a

Department of Civil and Environmental Engineering, Newark College of Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA Department of Civil and Environmental Engineering, Rowan University, Glassboro, NJ 08028, USA Department of Chemistry and Biochemistry, Rowan University, Glassboro, NJ 08028, USA d Environmental Science Bureau, New York State Department of Transportation, Albany, NY 12232, USA b c

H I G H L I G H T S • • • •

Concentration and distribution of trace metals in the paint waste were addressed. The elevated Fe is attributed to the steel grit used as abrasive blasting material. Statistical analysis indicated that Pb and Cr areassociated in the paint waste. The observation raises concern of leaching from this waste stream.

a r t i c l e

i n f o

Article history: Received 19 January 2015 Received in revised form 31 March 2015 Accepted 31 March 2015 Editor: F.M. Tack Keywords: Bridge Paint waste Metal Pigment Minerals

a b s t r a c t Between 1950 and 1980, lead and chromium along with other metals have been used in paint coatings to protect bridges from corrosion. In New York State with 4500 bridges in 11 Regions 2385 of the bridges have been rehabilitated and subsequently repainted after 1989 when commercial use of lead based paint was prohibited. The purpose of this research was to address the concentration and distribution of trace metals in the paint waste generated during bridge rehabilitation. Using hypothesis testing and stratified sampling theory, a representative sample size of 24 bridges from across the state was selected that resulted in 117 paint waste samples. Field portable X-ray fluorescence (FP-XRF) analysis revealed metal concentrations ranged from 5 to 168,090 mg kg−1 for Pb, 49,367 to 799,210 mg kg−1 for Fe, and 27 to 425,510 mg kg−1 for Zn. Eighty percent of the samples exhibited lead concentrations greater than 5000 mg kg−1. The elevated iron concentrations may be attributed to the application of steel grit as an abrasive blasting material routinely used by state Departments of Transportation in the paint removal process. Other metals including Ba and Cr were observed in the paint waste as well. As a result of the paint formulation, metals were found to be associated in the paint waste (Pb correlated with Cr (r = 0.85)). The elevated metal concentrations observed raises concern over the potential impact of leaching from this waste stream. © 2015 Elsevier B.V. All rights reserved.

1. Introduction The general practice for protecting steel bridges from corrosion involves applying paint coatings (Boxall and Von Fraunhofer, 1980; Gooch, 1993; Lambourne and Strivens, 1999). Between 1950 and 1980, these paint coatings used a number of metals including lead and chromium for corrosion protection. However, concerns stemming from human health impacts of lead-based paint (LBP) prompted its ban from most applications in the United States in 1978 (Davis et al.,

⁎ Corresponding author. E-mail address: [email protected] (L. Axe).

http://dx.doi.org/10.1016/j.scitotenv.2015.03.144 0048-9697/© 2015 Elsevier B.V. All rights reserved.

1993; Hall, 1972; Jacobs et al., 2002). Lead release from LBP has been associated with health effects including damage to the brain and central nervous system in children, reproductive problems, and high blood pressure (Mielke and Gonzales, 2008; Mielke et al., 2001). In addition, during aging and weathering, paints tend to chalk, chip, flake, and otherwise deteriorate, resulting in an accumulation of pigment material in soils and surface water surrounding painted structures (Hopwood et al., 2003; Kyger et al., 1999). In response to these concerns, the Department of Housing and Urban Development (HUD) and Consumer Product Safety Commission (CPSC) prohibited residential use of LBP since 1978 (CPSC, 1977; National Institute for Occupational Safety and Health (NIOSH), 1992). In New York State, LBP has been prohibited from commercial use since 1989 (New York State Department of Transportation (NYSDOT), 1988).

Z. Shu et al. / Science of the Total Environment 526 (2015) 262–270

In NYS, as the paint on steel bridges reaches a critical level of deterioration, rehabilitation involves abrasive blasting, which is one of the most effective paint removal approaches (Appleman, 1992). In the blasting operation, abrasive particles are propelled against the surface using a concentrated stream of compressed air. Dust, abrasive, and paint debris are vacuumed simultaneously. Debris is separated for disposal and the abrasive particles are returned for reuse. In NYS, recycled steel grit (i.e., martensite (Society of Automotive Engineers (SAE), 2006)) (comprised by wt. of Fe (N96%), C (b1.2%), Mn (b1.3%), Si (b1.2%), Cr (b0.25%), Cu (b0.25%), and Ni (b0.2%) (Dunkerley et al., 1978)), is applied routinely (NYSDOT, 1988, 2008) as blasting material during the paint removal procedure. Although magnetic separation is used to remove abrasive material particles, a fraction of steel grit remains with paint waste. The paint waste is therefore comprised of paint and the blasting abrasive material steel grit. Paint waste remains a pervasive problem in U.S. cities (Axe et al., 2009; Caravanos et al., 2006; Ferlauto, 1994; Mielke and Gonzales, 2008; Mielke et al., 2001; Townsend et al., 2004), and an increasing problem in the developing world where LBP is still manufactured and used (Adebamowo et al., 2007; Clark et al., 2006; Nduka et al., 2008). For example, of the 25 exterior paints studied in New Orleans (Mielke and Gonzales, 2008), only one sample revealed lead concentrations less than the HUD (2003) action level of 5000 mg kg−1. Caravanos et al. (2006) evaluated lead deposition in ambient dust in New York City boroughs from 2003–2004 and observed concentrations ranging from 138 μg m−2 to 7858 μg m−2. Given the HUD/EPA dust standard of 431 μg m−2 (U.S. EPA/HUD, 2003), bridge rehabilitation and other construction/demolition activities are potential sources for lead and may in part explain lead deposition in this area (Caravanos et al., 2006). In addition to Pb, other metals such as Cr, Ba, and Zn in paint are potential sources of pollution during rehabilitation as well (Mielke et al., 2001; Fjelsted and Christensen, 2007; Ojeda-Benítez et al., 2013). Therefore, evaluating concentration and distribution of metals in the paint waste generated during bridge rehabilitation is necessary. Studies of paint particles/associated waste have focused on the distribution of Pb (Bernecki et al., 1995; Beckley and Groenier, 2008; Brumis et al., 2001; Daniels et al., 2001; MnDOT, 2004) with occasional measurements of other metals such as As, Cr, Cd, Hg, and Zn (Conroy et al., 1996; Mielke and Gonzales, 2008; Turner and Sogo, 2012). Mielke and Gonzales (2008) found that Pb concentrations were independent of Hg in interior and exterior paint sampled from New Orleans homes. On the other hand, Turner and Sogo (2012) reported correlations between Pb and Cu in exterior paint of urban structures in the UK. These previous studies have demonstrated the presence of elevated Pb in subsurface coatings, however, a systematic analysis of paint waste generated throughout a region or state has not been conducted for bridges under rehabilitation. In addition, previous studies (Bernecki et al., 1995; Martel et al., 1997) have not included analyses to evaluate metal association and dominant forms present in the paint waste. Therefore, in this study as NYS is working with 4500 bridges that will undergo rehabilitation on some regular basis, the objective of this research is to characterize the paint waste for concentration and distribution of metals. FP-XRF was applied to detect and quantify concentrations in the painted surface and subsurface. Statistical analyses were employed to evaluate the factors that affect metal distribution. Further analysis was conducted using X-ray diffraction (XRD) for mineralogy and field emission scanning electron microscopy (FE-SEM) with energy dispersive X-ray analysis (EDX) to investigate surface coating composition and morphology critical in addressing surface interactions and metal mobility. The results from this study provide fundamental knowledge on the characterization of paint waste needed for subsequent leaching studies (Shu et al., 2014, 2015). The first step in addressing metal mobility is to evaluate metal concentrations and distribution as well as the degree to which metals are present at potentially elevated concentrations.

263

2. Materials and methods Laboratory quality assurance and quality control procedures are based on the American Society for Testing and Materials methods (American Society for Testing and Materials (ASTM), 1990). All reagents were of certified analytical grade or trace metal quality. Containers were soaked in a 10% HNO3 solution for 48 h when using glassware and 24 h for Nalgene® high-density polyethylene (HDPE) containers, then rinsed in Millipore-Q water, dried, and stored in a particle-free environment before use. 2.1. Sample collection and preparation To obtain a statistically representative number of samples for the study, hypothesis testing and stratified sampling theory was applied for the sample size estimation. With 11 Regions and 2385 bridges rehabilitated and subsequently repainted after 1989, 24 bridges from across the NYS were selected for this study based on the statistical analysis (details are provided in Supporting Information). Between October 2010 and November 2011, 117 samples of paint waste were obtained from 24 bridges under rehabilitation from seven regions (Regions 1, 2, 3, 5, 7, 10, and 11) in NYS (details are provided in Supporting Information Fig. S1). All bridges in the study have been repainted at least once since 1989, when NYS prohibited the commercial use of LBP (NYSDOT, 1988). Duplicate (paint waste) samples were collected from five random locations (directly from bridge surface or collected waste in 50 gal drums) at each bridge site selected. Specifically, two samples were obtained from the same drum location or bridge site with trowels. In total, ten samples were collected for each bridge (four samples for Bridge 3–3) and stored in Nalgene® high-density polyethylene (HDPE) containers at 4 °C (American Society for Testing and Materials (ASTM), 1990). 2.2. Total metal concentrations Field portable X-ray fluorescence (FP-XRF) is one of the most effective approach to measure Pb and other metal concentrations in paint (Beckley and Groenier, 2008; Brumis et al., 2001; Daniels et al., 2001; Minnesota Department of Transportation (MnDOT), 2004). FP-XRF has proven effective for in situ analysis as demonstrated in field and laboratory results (i.e., R2 = 0.976–0.992 for Pb (Markey et al., 2008) and R2 = 0.843–0.996 for As, Pb, and Zn (Radu and Diamond, 2009)). An advantage of the XRF technique is its ability to probe metal concentrations on the surface as well as subsurface; thus, it has the capability to characterize a wide range of remaining pigments. To investigate the metal distribution in the paint waste, Ba, Cr, Pb, Fe, and Zn were analyzed with the NITON XL3t-600 series FP-XRF following EPA Method 6200 (U. S. EPA, 1998) using either Soil Mode (metal concentrations b 2% by wt.) or Mining Mode (metal concentrations ≥ 2% by wt.). The calibration was verified by analyzing NIST certified reference material (SRM). Additional details including detection limits for the FP-XRF in these two modes are provided in Supporting Information (Tables S1 and S2). Each sample was homogenized by using the four quarter method (Popek, 2003) to represent the sampling interval. The paint samples were loaded into 12 ml sample holders (SC-4331), sealed with transparent membranes, and analyzed for 180 s. The XL3t-600 FP-XRF frame is used to support the analyzer during the detection procedure for continuous analysis. The instrument combines advanced electronics and provide a continuum of X-rays across a broad range of energies with a maximum output of 50 keV. Filters were applied between the X-ray tube and the sample to suppress the continuum radiation while passing the characteristic X-rays from the anode. It is important to note that both Soil Mode and Mining Mode combine fundamental parameters (FP) mode with Compton normalization (for background matrix automatic correction), which provides improved accuracy for samples ranging from less than 2% by wt.

264

Z. Shu et al. / Science of the Total Environment 526 (2015) 262–270

10000

Fe

Low Range Filter

Ti Pb Fe Cr Pb Ca Ca Pb Cu Si Ar Pb

1000 100 10 1 1000

Pb

Fe

Pb

Fe

Pb

100

Ti CaCr

10

Main Range Filter

Ba

Zn Pb Ag Sr

Ca

Counts

1 1000

Fe

100

Ba

High Range Filter

Pb Pb

Cr Fe Ti Zn Pb Ca

10

Ag

Pb Ba

Mo

Ca

Ba

Mo

1 1000

Ar

Light Range Filter

Fe Ti Fe Ti

100

10

1 0

5

10

15

20

25

30

35

40

45

50

Emission Energy KeV Fig. 1. Representative XRF spectra obtained from the paint waste samples using NITON XL3t-600 series FP-XRF. X-ray tubes produce a continuum of X-rays across a broad range of energies with a maximum output of 50 keV. Filters were applied between the X-ray tube and the sample to suppress the continuum radiation while passing the characteristic X-rays from the anode.

to greater than 2% wt. Pb was also analyzed with a NITON XLp-300 FPXRF, which excites the K shell fluorescent X-rays of Pb. This analyzer has a 40 mCi cadmium-109 radioisotope source with X-ray emission from approximately 22.5 and 88.1 keV. Results from using FP-XRF on eight paint samples with Pb concentrations ranging from 210 to 168,093 mg kg− 1 were compared to applying digestion with hydrofluoric acid (HF) (Method 3052) (U.S. EPA, 2004) followed by inductively coupled plasma mass spectroscopy (ICP-MS) (Method 6020A) (U.S. EPA, 2007). FP-XRF correlated (R = 0.85 to 0.98) (Details are provided in Supporting Information) with the ICP-MS analysis (Fig. S2 and S3 in Supporting Information). In addition, the measured elements distinguished in the XRF Spectra (Fig. 1) demonstrate the effectiveness of using FP-XRF as a field method to analyze the Pb, Cr, Ba, Fe, and Zn concentrations in bridge paint waste. 2.3. Principle component analysis (PCA) The composition of the paint waste is complex and heterogeneous. To identify possible factors that affect the distribution of trace elements in paint waste, PCA was applied in this study. The analysis involves a mathematical procedure that transforms a number of potentially correlated variables into a smaller number of uncorrelated variables (principal components (PCs)) (Torrecilla et al., 2009), which are linear combinations of the original variables. The eigenvalues are used to

determine the percentage as well as cumulative percentage of variances, where PCs with eigenvalues greater than 1 are selected (Kaiser, 1960). The eigenvalues reflect the quality of the projection from the N-dimensional initial table to a lower number of dimensions. The PC with the greatest eigenvalue is considered the most significant. The eigenvalues and the corresponding factors are sorted by descending order to the degree to which the initial variability is represented (converted to %). In this study, PCA was applied on total metal concentrations (i.e., Ba, Cr, Fe, Pb, Zn, Ti, and Ca) in the paint waste samples.

Table 1 Quartile distribution of trace metals in paint waste from NYS (n = 117). Metal

Mean Minimum 25th percentile Median 75th percentile Maximum

Metal concentrations (mg kg−1) Ba

Cr

Fe

Pb

Zn

6431 BDL 2797 5785 9410 16,319

3018 BDL 490 2455 5268 10,192

244,929 49,367 133,125 245,820 329,765 799,210

46,060 BDL 9058 45,870 73,693 168,093

85,530 27 32,233 51,467 85,458 425,507

BDL refers to below detection limit. Detection limits (mg kg−1) for this study: Ba = 100, Cr = 85, Pb = 13, Fe = 75, Zn = 25.

Z. Shu et al. / Science of the Total Environment 526 (2015) 262–270

2.4. Metal forms and association in the paint waste

Metal Concentrations (mg kg 1)

Toxicity of metals strongly depends on their speciation in the paint waste. To assess minerals of Pb, Cr, and iron oxides present and formed on the steel grit surface, PANalytical Empyrean X-ray diffraction (XRD) system was applied on the samples with the greatest concentrations of Pb, Cr, and Fe. Steel grit was separated from the paint waste using a magnetic bar. Fe oxide minerals were selected based on thermodynamic

2 x 10

5

1.5 x 10

5

1 x 10

5

5 x 10

4

265

stability in the paint waste. The paint waste was loaded in the sample holders with the back filling technique. Diffraction data were obtained by step-scans using Cu K-α radiation generated at 45 keV and 40 mA scanning from 10° to 100° 2θ. The (hkl) planes corresponding to peaks were calculated and compared with the standard powder diffraction file (PDF) (JCPDS, 1998). Further identification was conducted by the comparing each of the diffractograms to the powder diffraction database. To isolate iron oxides formed on the steel grit surface, background

Pb

0 4 1.2 x 10 4 Cr 1 x 10 8000 6000 4000 2000 0 5 5 x 10

4 x 10

5

3 x 10

5

2 x 10

5

1 x 10

5

Zn

0 4 2 x 10 1.5 x 10

4

1 x 10

4

Ba

5000 0 5 9 x 10 6 x 10

5

3 x 10

5

0

Fe

2-1 2-2 5-1 5-2 5-3 5-4 5-5 1-1 3-1 3-2 3-3 7-1 7-2 10-1 10-2 10-3 10-4 10-5 10-6 10-7 10-8 10-9 11-1 11-2

SSPC SP 10

SSPC SP 6

Bridge ID Five samples: a

b

c

d

e

Fig. 2. Total concentrations of Pb, Cr, Zn, Ba, and Fe in paint are shown as a function of the five locations for bridges in Regions 1, 2, 3, 5, 7, 10, and 11 using NITON XL3t-600 series FP-XRF (Pb was also detected by NITON XLp-300 FP-XRF). Mining Mode was used for sample with metal concentrations greater than 2% by wt., while Soil Mode was applied for samples with concentrations less than 2% by wt. Bridge ID represents the Region number and bridge sampled in this Region. All bridges sampled were rehabilitated after 1989. Blasting standard SSPC SP 10 was applied for bridges in Regions 2 and 5, while SSPC SP 6 was used for bridges in Regions 1, 3, 7, 10, and 11 (Pb was also detected by NITON XLp-300 FP-XRF). LBP is defined as paint with Pb concentrations greater than 0.5% by wt. (5000 mg kg−1) (HUD, 2003).

266

Z. Shu et al. / Science of the Total Environment 526 (2015) 262–270

subtraction (i.e., SiO2 (silica), Zn (spelter), and Fe (martensite)) and normalization was conducted. Based on the peak and area analysis, semiquantitative results were obtained on the iron oxide minerals present. The LEO 1530 FE-SEM equipped with EDX (Inca series 200) was utilized to further investigate the morphology and metal association in the paint waste (a resolution of 2.5 nm at 5 keV, 1.2 nm at 20 keV; and 3 nm at 1 keV). To ensure the surface was conductive, samples were coated under high vacuum with a layer of carbon using an Edward's 12E6/ 1266 coating unit. 3. Results and discussion 3.1. Metal distribution in the paint waste Concentrations of most metals in paint ranged over several orders of magnitude (Table 1): 5 to 168,090 mg kg−1 for Pb, 49,367 to 799,210 mg kg−1 for Fe, and 27 to 425,510 mg kg−1 for Zn. Other elemental compounds of Ba and Cr, were also detected (Table 1): less than 100 (detection limit) to 16,319 mg kg− 1 for Ba and 21 to 10,192 mg kg−1 for Cr. The observed Pb concentrations (Fig. 2) are a consequence of its wide application as a corrosion inhibitor in paint before the 1980s (Gooch, 1993; Lambourne and Strivens, 1999). Even though rehabilitation and subsequent repainting were conducted more than once since 1989 for bridges studied in NYS, 94 out of 117 paint samples exhibited lead concentrations greater than 5000 mg kg−1, which is an action limit from HUD (NIOSH, 1992). The elevated Fe found in samples may have come from a number of sources: black iron oxide (Fe2O3 [synthetic] + MnO2 [pyrolusite]) at 10–15% (by wt.) is used in the paint formulation (Boxall and Von Fraunhofer, 1980), rust from the bridge structure, and the steel grit blasting abrasive (Appleman, 1992, 1997). Typically steel (cast steel) grit is comprised by wt. of Fe (N 96%), C (b1.2%), Mn (b 1.3%), Si (b1.2%), Cr (b0.25%), Cu (b0.25%), and Ni (b0.2%) (Dunkerley et al., 1978). In New York, steel grit is typically used as the blasting abrasive (NYSDOT, 2008). In addition to steel grit, other abrasives used throughout the country include Black Beauty (a mixture of Fe oxide, Al oxide, Ca oxide, and silicon dioxide), boiler slag, sand, furnace slag, aluminum oxide, and garnet (Iowa Department of Transportation (IADOT), 2006; MnDOT, 2004; U.S. EPA, 1997). The observed Zn concentrations in the waste reflects the increasing usage of Zn primer on the bridges (Lambourne and Strivens, 1999; Turner and Sogo, 2012). Overall, concentrations of Pb and Zn are consistent with the similar studies (Supplementary Material, Table S3) (Bernecki et al., 1995; Brumis et al., 2001; Mielke and Gonzales, 2008; Mielke et al., 2001), whereas Fe concentrations obtained in this study are greater than that observed by Bernecki et al. (1995) and Turner and Sogo (2012) (Supplementary Material, Table S3). The results may be attributed to the elevated steel grit concentrations remaining in the paint waste, which to some extent dilutes the concentrations of other metals (such as Pb and Zn). Because the steel grit added increased iron to as great as 80% by weight in samples, other metal concentrations in these same samples would therefore decrease. Cr is consistent with or greater than the concentrations in the residential paint (Brumis et al., 2001; Mielke et al., 2001; Turner and Sogo, 2012). Because most work has focused on Pb, an analysis of Ba concentrations in paint waste has seldom been reported (Conroy et al., 1996; Mielke et al., 2001). Interestingly, concentrations of Pb and Cr in the paint waste samples follow a similar trend. As expected, the surface preparation method is an important factor that affects the degree to which paint remains on the bridge surface. The Society for Protective Coatings (SSPC) surface preparation standard SP-6 (Commercial Blast Cleaning) (NYSDOT, 2008) has been applied on bridges in NYS prior to 2006, where paint and rust from steel were removed to a residual of 33% of the total area. After 2006, SSPC SP-10 (Near White Blast Cleaning) has been required in the blasting procedure (NYSDOT, 2008) for all regions in NY. SP-10 restricts the visible residue

remaining on the bridge surface to 5% of the total area (methods refer to the ones applied in the previous rehabilitation, which determines residual on the bridge). Consequently, for the 24 bridges studied, 99% of the paint samples from the bridges blasted with SSPC SP-6 (Regions 1, 3, 7, 10, and 11) revealed Pb concentrations greater than the HUD limit of 5000 mg kg− 1 (NIOSH, 1992), while 37% of the paint samples from the bridges blasted with SSPC SP-10 (Regions 2 and 5) exhibited Pb concentrations greater than 5000 mg kg−1 (Fig. 2; Table 1). Significant variability (Fig. S4 through S6 in Supporting Information) in metal concentrations was observed across a single bridge. For example at Bridge 2-1, Pb ranged from 43% to 127% by wt., while Zn varied from 0.2 to 10% by wt. For the 24 bridges studied throughout NYS, because one sample per bridge cannot adequately describe metal concentrations, five locations were sampled in duplicate. In addition, the t-test was applied on the samples that are sorted by region. No significant difference was observed for metal concentrations between the regions studied (Region 2 and 5; Region 1, 3, 7, 10, and 11). This result indicated metal concentrations were not distributed as function as a region. Given the extent of bridges with elevated concentrations, managing the waste stream is an issue for the NYSDOT (Axe et al., 2009). 3.2. Statistical analysis of the metal distribution and association To further investigate the metal distribution and association, correlations were evaluated between metals in the paint waste. Pearson's correlation matrix (Table 2) indicated that Pb correlated with Cr (r = 0.85). Similar results have been reported by Bhuiyan et al. (2011) with observed correlation between Pb and Cr (r = 0.71). As a result of their findings, Bhuiyan et al. (2011) hypothesized that the paint industry may be one of the sources of contamination in the water distribution system in Dhaka, Bangladesh. In our study, paint applied in NYS has a similar composition to that found by Turner and Sogo (2012), where Cr, Pb, Fe, and Zn were observed in the exterior paints in urban areas in the UK. The trends were found across all regions in NYS indicating consistent application of Pb and Cr as pigments and extenders in the paint formulation. On the other hand, correlations were not observed between Pb, Fe, and Zn concentrations (r b 0.37, Table 2) suggesting unique sources in the paint waste. PCA showed essentially two main constituent axes with eigenvalues greater than 1 (Table 3), together explaining 60.2% of the data variance (or variability). The first eigenvalue of 2.82 represents 40.2% of the total variability. This result demonstrates that if the data were illustrated with one axis, 40.2% of the total variability in the data can be explained. Correlations greater than 0.50 (Table 3) are considered to demonstrate significant influence. The first PC (axis) revealed strong relationships with the associated total concentration present in the waste (e.g., Cr and Pb) (Table 3). These results are attributed to the paint formulation and the surface preparation standard applied to the bridges. As a result of the paint formulation and surface preparation, groups of metals were found to be associated in the paint waste. The second PC (axis) (Table 3) revealed the influence of Fe in the paint waste demonstrating that it is an important factor impacting metal distribution. Because of the varying concentration of steel grit remaining in the samples, from 5% to 80% by weight, RCRA metals in the paint waste vary as well. Using PCA analysis, Table 2 Pearson's correlation coefficient (r) for the selected metals in the paint waste.

Pb Ba Cr Fe Zn

Pb

Ba

Cr

Fe

Zn

1.00 0.43 0.85 0.24 0.37

1.00 0.44 0.02 0.32

1.00 0.30 0.42

1.00 0.29

1.00

Pearson's correlation coefficient (r) is significant at p b 0.001. r greater than 0.60 is highlighted as significant number.

Z. Shu et al. / Science of the Total Environment 526 (2015) 262–270

267

distribution (Fig. 2) and association (Fig. 4), where these two factors played important roles.

Table 3 Principal component analysis of selected metals in the paint waste samples. Variable

PC 1

PC 2

Ba Ca Cr Fe Pb Ti Zn Eigenvalue Proportion Cumulative

0.389 −0.031 0.541 −0.136 0.529 0.366 −0.351 2.82 0.402 0.402

−0.219 −0.061 0.131 −0.76 0.141 0.094 0.057 1.4 0.199 0.602

3.3. Metal forms in the paint waste While understanding the metal distribution and its association in the paint waste are important, most critical is the metal form which affects its potential mobility upon disposal. Toxicity of metals is dependent on the chemical form in the paint waste. XRD results revealed the presence of pigment minerals used before 1989 when lead-based paint was prohibited in NYS (NYSDOT, 1988) (Fig. 3). It is important to note that the XRD results demonstrate consistent minerals in the paint waste samples (Supplementary Material, Tables S5 through S7). Specifically, Pb and Cr occurred with similar trends in the paint waste (Fig. 3), which is consistent with Pearson's and PCA analysis. Specifically, Pb was observed as lead tetraoxide (Pb3O4(s)) and in association with Cr(VI) as crocoite (PbCrO4(s)). These results are expected as lead tetraoxide (or red lead Pb3O4, Pb2O4, PbO2·2PbO(s)) and lead

Correlation values greater than 0.50 are highlighted.

the most important factors accounting for total variability are the surface preparation standard (reflected in Table 3 (PC1)) and steel grit (iron) remaining in the paint waste (reflected in Table 3 (PC 2)). These results are consistent with the observations of the metal

Fe SiO

2

SiO

Pb

2

Paint sample 3-2 e

Ca AlZn Pb M

MFe

Al Fe

Fe

Fe

Relative intensity

F

Paint sample 5-2 d

M

H F M

Fe

H

H

Fe

F

Fe

Fe F

G

Paint sample 5-5 d

M

F FM

G

Fe

L LLCrCr

Cr

Paint sample 11-2a

L Cr LCr

L Cr

Fe

Fe

L Cr

L

20

Paint sample 11-2 e 40

60

80

100

2 Theta Fe – Fe SiO2 – SiO2 Pb – Pb3O4 L – PbCrO4 PbO H – hematite [Fe2O3] •

Ti – TiO2 Ca – CaCO3 Al - Al Cr – Cr2O3 M – magnetite [Fe3O4] F – ferrihydrite [5Fe2O3 9H2O] G – goethite [FeO(OH)] •

Fig. 3. XRD analysis of the primary minerals, Pb, Cr, and iron oxide in paint waste samples from Regions 3, 5, and 11.

268

Z. Shu et al. / Science of the Total Environment 526 (2015) 262–270

Table 4 Summarized XRF and XRD results. Identified matrix phases from XRD

Metal-bearing phases in paint waste XRF elements

Miner minerals measured from XRD*

Quartz (SiO2), Rutile (TiO2) Calcite (CaCO3) Al (bauxite) Fe (martensite) Zn (spelter)

Pb

Lead tetroxide [Pb3O4] Pb2(CrO4)O Cr2O3 Zinc oxide [ZnO] Zinc chromates [ZnCr2O4] Magnetite [Fe3O4] Goethite [FeO(OH)] Hematite [Fe2O3] Ferrihydrite (5Fe2O3·9H2O) BaSO4 [(Ba,Pb)SO4]

Cr Zn Fe

Ba

chromate (PbCrO4·PbO(s)) are reported to be the most widely used corrosion-inhibiting pigments on metal structures painted before the 1980s (Gooch, 1993; Lambourne and Strivens, 1999) (Supplementary Material, Table S4). Lead chromate (PbCrO4(s)) was the dominate Cr mineral applied for bridge paint (Winchester, 1988) although Cr has also been applied as Cr2O3(s). The presence of Cr2O3(s) is partly attributed to the application of chromium oxide green (Cr2O3(s)) in paint providing the green pigment (Lambourne and Strivens, 1999). Degradation (reduction) of the pigment itself is another important explanation (Monico et al., 2011). Reduction of PbCrO4·PbO(s) to the trivalent state (Cr2O3(s)) in paint has been studied by others (Erkens et al., 2001; Monico et al., 2011; Somme-Dubru et al., 1981). The redox process is induced by heat, UV–visible light, contaminants, and SO2 (Erkens et al., 2001; Somme-Dubru et al., 1981). Monico et al. (2011) reported approximately two-thirds of chromate yellow pigment (PbCrO4·PbO(s)) in paintings from the 1910s was reduced to Cr(III) compounds such as Cr2O3·2H2O(s), and in some cases correlated to the presence of Ba (sulfate) and/or to that of aluminum silicate compounds. Nonetheless, the presence of Pb was consistent with Cr (Fig. 3).

Iron oxides observed in the paint waste included ferrihydrite (5Fe2O3·9H2O or Fe5HO8·4H2O), magnetite (Fe3O4), goethite (αFeO(OH)), and hematite (Fe2O3) (Fig. 3). These oxidation products are formed on the steel grit surface (Hartley and Lepp, 2008; Jambor and Dutrizac, 1998; Müller and Pluquet, 1998). Iron oxide (11% by wt.) (Supplementary Material, Table S3) has been studied extensively on steel surfaces (Cornelis et al., 2008; Komárek et al., 2013; Zhou and Haynes, 2010) because of its role in metal sequestration in soils. Iron oxide particularly the amorphous metastable mineral ferrihydrite is an important sorbent in the environment because of its large surface area, high affinity for metals, and an abundance of binding sites. Consequently, the presence of iron oxide may have a significant affect on contaminant mobility from the paint waste. At the same time, it is important to note that under the reducing conditions found in anoxic portions of landfills, iron oxides may be reduced, and release bound metals in the system (Charlatchka and Cambier, 2000; Ghosh et al., 2004). Iron cycling and metal sorption occurs at the interface for trace metals such as Pb and As (Catalano et al., 2011; Neumann et al., 2013). In addition to the Pb, Cr, and Fe minerals, XRD demonstrated the presence of other minerals including SiO2 (silica), Fe (martensite) (Society of Automotive Engineers (SAE), 2006), TiO2 (rutile), Al (bauxite), CaCO3 (calcite), and Zn (spelter)/ZnO (zincite) (Fig. 3, Table 4, Supplementary Material, Table S5). Generally, the composition of a paint can be described as the carrier (continuous phase) and pigment (discontinuous phase) (Lambourne and Strivens, 1999). The former includes binders (i.e., polymer chains such as long chain carboxylic acids and alkyd resins) and solvents (e.g., ether [–C–O–C]), while the latter is composed of extenders (or supplementary pigment, i.e., TiO2 and CaCO3), primary pigments (fine particle organic or inorganic, i.e., lithopone [ZnS mixed with BaSO4]), and additives (minor components) (Bentley, 1998; Clark, 1976). Morphologically the paint particles exhibit an irregular topography ranging from 0.05 to 1 mm (Fig. 4) and angular shape steel grit residue (Fig. 4) with diameters of 0.3 to 1 mm (Fig. 4). In this study, EDX observations of Si, Ti, Ca, and Al correlated with Pb and Cr (Fig. 4), which is consistent with findings from other studies (Franquelo et al., 2012; Turner and Sogo, 2012). Minerals such as CaCO3(s) and SiO2(s) may affect

b

a

c Fe

Cr

Si

Al

Zn

Ti

Pb

Ca

Fig. 4. FE-SEM images and EDX mapping on a representative paint waste sample. (a) FE-SEM image; (b) Blue particles represent the steel grit; green particles present the paint in the waste sample; (c) EDX mapping on paint waste sample from Region 7 (color images in mapping represent the corresponding elements).

Z. Shu et al. / Science of the Total Environment 526 (2015) 262–270

the metal mobility. For example, Andra et al. (2011) found that Ca was an important factor in the mobilization of Pb from alkaline soils in San Antonio, TX. The dissolution of CaCO3(s) results in an increase in pH. Therefore, although elevated metals were observed, the presence of a number of minerals in the paint waste, including iron oxide (ferrihydrite (5Fe2O3·9H2O or Fe5HO8·4H2O), magnetite (Fe3O4(s)), goethite (α-FeOOH(s)), and hematite (Fe2O3(s))), calcite (CaCO3(s)), and silica (SiO2(s)) affects the potential mobility of metals in the paint waste. It is important to note that the above observation is representative of paint waste samples collected throughout the study. 4. Conclusion and implications XRF is a reliable and effective approach to detect metals such as Ba, Cr, Pb, Fe, and Zn in paint waste. The results indicate that although the 24 bridges studied to date have been repainted after 1989, lead-based paint continues to require management. Eighty percent of paint waste samples exhibited lead concentrations greater than 5000 mg kg−1, suggesting that the SSPC SP-6 (where paint residual may be as great as 33% of the total area) does not result in sufficient paint removal. The elevated iron concentrations were also observed from the application of steel grit used to remove paint. Although elevated Pb is observed in this study, leaching may be impacted by the presence of iron and iron oxide coatings. However, before leaching is examined (Shu et al., 2015), the first step is to demonstrate the metal concentrations and distribution in paint waste as NYS is working with 4500 bridges that will undergo rehabilitation on some regular basis. Other compounds of Cr and Ba were observed in paint as pigments and preservatives as well. Pb concentrations were observed to correlate with Cr (r = 0.85). This trend was found across all the regions in NYS indicating consistent application of Pb and Cr as pigments and extenders in paint composition. XRD results further revealed pigments used before 1989 such as Pb3O4(s), PbCrO4·PbO(s), and Cr2O3(s). It is important to note that the results in this study were obtained from 24 representative bridges from 11 Regions in NYS, the remaining bridges in NYS rehabilitated after 1989 may have similar characteristics with regard to metal concentrations, distribution, and mineralogy. In addition, the data collected in this work are based exclusively on paint removal by steel grit blasting abrasive during bridge rehabilitation. Steel grit has been used as abrasive blasting material in a number of States (e.g., Connecticut, Georgia, Minnesota, New Jersey, Oregon, Washington, and Wisconsin). Therefore, this research may be beneficial for other state DOT's working with paint waste. Acknowledgments The authors would like to thank NYSDOT for providing funding for this research (RFP Number: C-08-19). The contents of this report reflect the views of the authors who are responsible for the facts and the accuracy of the data presented herein. The contents do not necessarily reflect the official views or policies of the NYSDOT or the Federal Highway Administration. Appendix A. Supplementary data Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.scitotenv.2015.03.144. References Adebamowo, E.O., Scott Clark, C., Roda, S., Agbede, O.A., Sridhar, M.K., Adebamowo, C.A., 2007. Lead content of dried films of domestic paints currently sold in Nigeria. Sci. Total Environ. 388, 116–120. American Society for Testing and Materials (ASTM), 1990. Standard practice for decontamination of field equipment used at nonradioactive waste sites. Designation D5088-90, West Conshohocken, PA.

269

Andra, S.S., Datta, R., Reddy, R., Saminathan, S.K., Sarkar, D., 2011. Antioxidant enzymes response in vetiver grass: a greenhouse study for chelant‐assisted phytoremediation of lead‐contaminated residential soils. Clean Soil, Air, Water 39, 428–436. Appleman, B.R., 1992. Bridge paint: removal, containment, and disposal. Transp. Res. Board 176. Appleman, B.R., 1997. Lead−based paint removal for steel highway bridges. Transp. Res Board. Axe, L., Jahan, K., Dusseau, R.A., 2009. Field methods for determining lead content in bridge paint removal waste. New York State Department of Transportation, Project No. C-08-19. Beckley, R., Groenier, J.S., 2008. In: United States Department of Agriculture Forest Service TDP (Ed.), Using XRF Hand-Held Devices To Detect Lead-Based Paint. Bentley, J., 1998. Introduction to Paint Chemistry: Principles of Paint Technology. CRC Press. Bernecki, T.F., Nichols, G., Prine, D., Shubinsky, G., Zdunek, A., 1995. Issues Impacting Bridge Painting: An Overview. Bhuiyan, M.A.H., Suruvi, N.I., Dampare, S.B., Islam, M., Quraishi, S.B., Ganyaglo, S., Suzuki, S., 2011. Investigation of the possible sources of heavy metal contamination in lagoon and canal water in the tannery industrial area in Dhaka, Bangladesh. Environ. Monit. Assess. 175, 633–649. Boxall, J., Von Fraunhofer, J.A., 1980. Paint Formulation: Principles and Practice. Godwin. Brumis, S., Scholz, P., Materna, B., 2001. Lead exposure during hot cutting of stripped steel. Appl. Occup. Environ. Hyg. 16, 502–505. Caravanos, J., Weiss, A.L., Blaise, M.J., Jaeger, R.J., 2006. A survey of spatially distributed exterior dust lead loadings in New York City. Environ. Res. 100, 165–172. Catalano, J.G., Luo, Y., Otemuyiwa, B., 2011. Effect of aqueous Fe (II) on arsenate sorption on goethite and hematite. Environ. Sci. Technol. 45, 8826–8833. Charlatchka, R., Cambier, P., 2000. Influence of reducing conditions on solubility of trace metals in contaminated soils. Water Air Soil Pollut. 118, 143–167. Clark, H.A., 1976. Paint compositions. Google Patents. Clark, C., Rampal, K., Thuppil, V., Chen, C., Clark, R., Roda, S., 2006. The lead content of currently available new residential paint in several Asian countries. Environ. Res. 102, 9–12. Conroy, L.M., Menezes-Lindsay, R.M., Sullivan, P.M., Cali, S., Forst, L., 1996. Lead, chromium, and cadmium exposure during abrasive blasting. Arch. Environ. Health 51, 95–99. Cornelis, G., Johnson, C.A., Gerven, T.V., Vandecasteele, C., 2008. Leaching mechanisms of oxyanionic metalloid and metal species in alkaline solid wastes: a review. Appl. Geochem. 23, 955–976. CPSC, 1977. Notice reducing allowable levels of lead. Final rule. Fed. Regist. 42 (1), 44199. Daniels, A.E., Kominsky, J.R., Clark, P.J., 2001. Evaluation of two lead-based paint removal and waste stabilization technology combinations on typical exterior surfaces. J. Hazard. Mater. 87, 117–126. Davis, J.M., Elias, R.W., Grant, L.D., 1993. Current issues in human lead exposure and regulation of lead. Neurotoxicology 14, 15. Dunkerley, F.J., Gaudino, A.J., Vilyus, R.P., 1978. Steel abrasive materials. Google Patents. Erkens, L., Hamers, H., Hermans, R., Claeys, E., Bijnens, M., 2001. Lead chromates: a review of the state of the art in 2000. Surf. Coat. Int. B Coat. Trans. 84, 169–176. Ferlauto, E., 1994. Lead-based paint and the lead abatement issue in the United States. J. Coatings Technol. 66, 69–74. Fjelsted, L., Christensen, T.H., 2007. Household hazardous waste: composition of paint waste. Waste Manag. Res. 25 (6), 502–509. Franquelo, M., Duran, A., Castaing, J., Arquillo, D., Perez-Rodriguez, J., 2012. XRF, μ-XRD and μ-spectroscopic techniques for revealing the composition and structure of paint layers on polychrome sculptures after multiple restorations. Talanta 89, 462–469. Ghosh, A., Mukiibi, M., Ela, W., 2004. TCLP underestimates leaching of arsenic from solid residuals under landfill conditions. Environ. Sci. Technol. 38, 4677–4682. Gooch, J.W., 1993. Lead-based Paint Handbook. Plenum Press, New York. Hall, S., 1972. Lead pollution and poisoning. Environ. Sci. Technol. 6, 30–35. Hartley, W., Lepp, N.W., 2008. Remediation of arsenic contaminated soils by iron-oxide application, evaluated in terms of plant productivity, arsenic and phytotoxic metal uptake. Sci. Total Environ. 390, 35–44. Hopwood, I., Palle, S., Younce, R., 2003. Environmental Impacts of Bridge Cleaning Operations. HUD, 2003. Lead Safety for Remodeling, Repair, and Painting. Iowa Department of Transportation (IADOT), 2006. Chapter 10, Construction Manual, October. http://www.iowadot.gov/erl/archives/oct_2006/CM/content/10-50.htm. Jacobs, D.E., Clickner, R.P., Zhou, J.Y., Viet, S.M., Marker, D.A., Rogers, J.W., et al., 2002. The prevalence of lead-based paint hazards in U.S. housing. Environ. Health Perspect. 110, A599–A606. Jambor, J.L., Dutrizac, J.E., 1998. Occurrence and constitution of natural and synthetic ferrihydrite, a widespread iron oxyhydroxide. Chem. Rev. 98, 2549–2586. JCPDS, 1998. Handbook for Diffraction Data (PCPDFWIN Ver. 2.00). Kaiser, H.F., 1960. The application of electronic computers to factor analysis. Educ. Psychol. Meas. Komárek, M., Vaněk, A., Ettler, V., 2013. Chemical stabilization of metals and arsenic in contaminated soils using oxides — a review. Environ. Pollut. 172, 9–22. Kyger, J.R., Rinke, S.D., Biagioni, R.N., Sheets, R.W., 1999. Soil Contamination From Paint on Highway Bridge, Symposia Papers Presented Before the Division of Environmental Chemistry American Chemical Society, Anaheim, CA. Lambourne, R., Strivens, T., 1999. Paint and Surface Coatings: Theory and Practice. Woodhead. Markey, A.M., Clark, C.S., Succop, P.A., Roda, S., 2008. Determination of the feasibility of using a portable X-ray fluorescence (XRF) analyzer in the field for measurement of lead content of sieved soil. J. Environ. Health 70, 24–29 (quiz 55-6). Martel, C.M., Atanassopoulos, C., Marinas, B.J., 1997. Mobility of Lead-based Paint in a Landfill. Solid Waste Association of North America, pp. 457–472.

270

Z. Shu et al. / Science of the Total Environment 526 (2015) 262–270

Mielke, H.W., Gonzales, C., 2008. Mercury (Hg) and lead (Pb) in interior and exterior New Orleans house paint films. Chemosphere 72, 882–885. Mielke, H.W., Powell, E.T., Shah, A., Gonzales, C.R., Mielke, P.W., 2001. Multiple metal contamination from house paints: consequences of power sanding and paint scraping in New Orleans. Environ. Health Perspect. 109, 973. Minnesota Department of Transportation (MnDOT), 2004. Air Quality and Waste Management for the Removal of Paint (Using Dry Abrasive Blasting) on Steel Bridge Structures. Monico, L., Van der Snickt, G., Janssens, K., De Nolf, W., Miliani, C., Verbeeck, J., et al., 2011. Degradation process of lead chromate in paintings by Vincent van Gogh studied by means of synchrotron X-ray spectromicroscopy and related methods. 1. Artificially aged model samples. Anal. Chem. 83, 1214–1223. Müller, I., Pluquet, E., 1998. Immobilization of heavy metals in sediment dredged from a seaport by iron bearing materials. Water Sci. Technol. 37, 379–386. National Institute for Occupational Safety and Health (NIOSH), 1992. In: Health NIfOSa (Ed.), Health Hazard Evaluation Report: HUD Lead-Based Paint Abatement Demonstration Project, DHHS (NIOSH) Pub. No. 90-070-2181. NIOSH, Cincinnati, OH. Nduka, J., Orisakwe, O., Maduawguna, C., 2008. Lead levels in paint flakes from buildings in Nigeria: a preliminary study. Toxicol. Ind. Health 24, 539–542. Neumann, A., Olson, T.L., Scherer, M.M., 2013. Spectroscopic evidence for Fe (II)–Fe (III) electron transfer at clay mineral edge and basal sites. Environ. Sci. Technol. 47 (13), 6969–6977. New York State Department of Transportation (NYSDOT), 1988. Specification for Bridges – Removal of Lead Based Paints – New Department Paint System for Structural Steel. Engineering Instruction. EI, p. 88-36. NIOSH, 1992. In: Health NIfOSa (Ed.), Health Hazard Evaluation Report: HUD Lead-Based Paint Abatement Demonstration Project, DHHS (NIOSH) Pub. No. 90-070-2181. NIOSH, Cincinnati, OH. NYSDOT, 2008. Standard Specification. Ojeda-Benítez, S., Aguilar-Virgen, Q., Taboada-González, P., Cruz-Sotelo, S.E., 2013. Household hazardous wastes as a potential source of pollution: a generation study. Waste Manag. Res. 31 (12), 1279–1284. Popek, E.P., 2003. Sampling and Analysis of Environmental Chemical Pollutants: A Complete Guide. Academic Press. Radu, T., Diamond, D., 2009. Comparison of soil pollution concentrations determined using AAS and portable XRF techniques. J. Hazard. Mater. 171, 1168–1171.

Sae Specification, 2006. J827 — High Carbon Steel Shot. http://www.blastmaster.net/ select/datasheets/93710.pdf. Shu, Z., Axe, L., Jahan, K., Ramanujachary, K.V., 2014. Field methods for rapidly characterizing paint waste during bridge rehabilitation. Chemosphere. http://dx.doi.org/10. 1016/j.chemosphere.2014.10.081 (in press). Shu, Z., Axe, L., Jahan, K., Ramanujachary, K.V., 2015. Metal leaching from the bridge paint waste in the presence of steel grit. Chemosphere 119, 1105–1112. Somme-Dubru, M., Genet, M., Mathieux, A., Rouxhet, P., Rodrique, L., 1981. Evaluation by photoelectron spectroscopy and electron microscopy of the stabilization of chromeyellow pigments. J. Coatings Technol. 53, 51–56. Torrecilla, J.S., García, J., Rojo, E., Rodríguez, F., 2009. Estimation of toxicity of ionic liquids in leukemia rat cell line and acetylcholinesterase enzyme by principal component analysis, neural networks and multiple lineal regressions. J. Hazard. Mater. 164, 182–194. Townsend, T., Tolaymat, T., Leo, K., Jambeck, J., 2004. Heavy metals in recovered fines from construction and demolition debris recycling facilities in Florida. Sci. Total Environ. 332, 1–11. Turner, A., Sogo, Y., 2012. Concentrations and bioaccessibilities of metals in exterior urban paints. Chemosphere 86, 614–618. U. S. EPA, 1998. Method 6200, Field Portable X-ray Fluorescence Spectrometry for the Determination of Elemental Concentrations in Soil and Sediment (EPA/600/R-97/150, Revision 0), Retrieved November 1, 2007. U.S. EPA, 1997. Emissions Factors & AP 42, Compilation of Air Pollutant Emission Factors, Chapter 13: Miscellaneous Sources. U.S. EPA, 2004. Method 3052 Microwave-Assisted Acid Digestion of Siliceous and Organically Based Matrices, Washington, DC. U.S. EPA, 2007. Method 6020A inductively coupled plasma-mass spectrometry. SW-846 Chapter 3. Winchester, C.M., 1988. Nitrocellulose-urethane traffic paint. Google Patents. Zhou, Y., Haynes, R.J., 2010. Sorption of heavy metals by inorganic and organic components of solid wastes: significance to use of wastes as low-cost adsorbents and immobilizing agents. Crit. Rev. Environ. Sci. Technol. 40, 909–977.