Real time analysis of lead-containing atmospheric particles in Guangzhou during wintertime using single particle aerosol mass spectrometry

Ecotoxicology and Environmental Safety 168 (2019) 53–63

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Ecotoxicology and Environmental Safety journal homepage: www.elsevier.com/locate/ecoenv

Real time analysis of lead-containing atmospheric particles in Guangzhou during wintertime using single particle aerosol mass spectrometry

T

Jianglin Lua,b,c,1, Li Maa,b,c,1, Chunlei Chenga,c, Chenglei Peid,e,f, Chak K. Chang, Xinhui Bid, ⁎ Yiming Qinh, Haobo Tani, Jingbo Zhouj, Mubai Chenk, Lei Lia,c, Bo Huanga,c, Mei Lia,b,c, , Zhen Zhoua,c a

Institute of Mass Spectrometer and Atmospheric Environment, Jinan University, Guangzhou 510632, China State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China c Guangdong Provincial Engineering Research Center for Online Source Apportionment System of Air Pollution, Guangzhou 510632, China d State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Resources Utilization and Protection, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, PR China e University of Chinese Academy of Sciences, Beijing 100049, China f Guangzhou Environmental Monitoring Center, Guangzhou 510030, China g School of Energy and Environment, City University of Hong Kong, Hong Kong, China h School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA i Guangdong Ecological Meteorology Center, Guangzhou 510080, China j Shijiazhuang Environmental Monitoring Station of Hebei Province, Shi Jiazhuang 050022, China k College of Chemistry and Environment Protection Engineering, Southwest Minzu University, Chengdu 610225, China b

A R T I C LE I N FO

A B S T R A C T

Keywords: Lead-containing particles Single particle aerosol mass spectrometry Source apportionment Mixing state Diurnal pattern Guangzhou

The toxic effects of lead on human health and the environment have long been a focus of research. To explore sources of lead in Guangzhou, China, we investigated atmospheric lead-containing particles (LCPs) during wintertime using a single particle aerosol mass spectrometer (SPAMS). Based on mass spectral features, LCPs were classified into eight major particle types, including Pb-Cl and Pb-Cl-Li (coal combustion and waste incineration), Pb-Cl-EC and Pb-Cl-OC (diesel trucks and coal combustion), Pb-Cl-Fe (iron and steel industry), PbCl-AlSi (dust), Pb-Sec (secondary formation), and Pb-Cl-Zn (industrial process); these sources (in parentheses) were identified by comparing atmospheric LCP mass spectra with authentic Pb emission source mass spectra. Sampling periods with LCP number fractions (NFs) more than three times the average LCP NF (APF = 4.35%) and below the APF were defined as high LCP NF periods (HLFPs: H1, H3, and H5) and low LCP NF APF periods (LLFPs: L2 and L4), respectively. Diurnal patterns and high Pb-Sec content during LLFPs indicate that photochemical activity and heterogeneous reactions may have controlled Pb-Sec particle formation. The inverse Pb-Cl and Pb-Sec particle diurnal trends during LLFPs suggest the replacement of Cl by sulfate and nitrate. On average over the five periods, ~ 76% of the LCPs likely arose from coal combustion and/or waste incineration, which were dominant sources during all five periods, followed by diesel trucks during LLFPs and iron- and steel-related sources during HLFPs; HLFP LCPs arose mainly from primary emissions. These results can be used to more efficiently control Pb emission sources and prevent harm to human and environmental health from Pb toxicity.

1. Introduction Heavy metals, which are ubiquitously present in atmospheric particulate matter (PM), can cause harmful effects and persistent toxicity in human beings (Barregard et al., 2010; Grandjean and Herz, 2015). Lead (Pb), one of the most hazardous heavy metals, has been studied

extensively (Murphy et al., 2007; Li et al., 2012a; Wang, 1984; Daland Juberg et al., 1997). Pb can be adsorbed onto atmospheric particles and enter the body through PM inhalation (Csavina et al., 2014). High amounts of Pb can cause severe damage to the central nervous System (Roper et al., 1991; Gillis et al., 2012). Children with higher bone Pb levels display more aggressive delinquent behavior (Nevin, 2000). igher

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Corresponding author at: Institute of Mass Spectrometer and Atmospheric Environment, Jinan University, Guangzhou 510632, China. E-mail address: [email protected] (M. Li). 1 The authors contributed equally to this work. https://doi.org/10.1016/j.ecoenv.2018.10.006 Received 19 July 2018; Received in revised form 30 September 2018; Accepted 2 October 2018 Available online 26 October 2018 0147-6513/ © 2018 Elsevier Inc. All rights reserved.

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Fig. 1. Average positive and negative mass spectra of major LCP types.

source. Leaded gasoline was phased out in China in 2000, after which total emissions of Pb into the atmosphere declined sharply, rendering coal combustion dominant Pb source (Cho et al., 2011; Li et al., 2012b). However, high atmospheric Pb concentrations are still observed in some places. For example, in January 2013, the Beijing monthly average Pb concentration in PM2.5 was 369 ± 288 ng/m3 with a daily maximum concentration of 1.3 μg/m3 (Cai et al., 2017), which is comparable to concentrations observed in Beijing in the early 2000s (Sun et al., 2006). The elimination of leaded gasoline thus provides a valuable opportunity to fully understand ambient Pb sources that were previously masked by dominant gasoline Pb source. Guangzhou is one of the largest industrial cities in southern coastal

postnatal blood Pb levels are associated with lower IQ scores in children under 6 years old (Huang et al., 2012). Health risks from ambient heavy metal pollution, including Pb, V, Cr, Mn, etc., have been evaluated in the literature (Xu et al., 2016; Li et al., 2015). Lead-containing particles (LCPs) also serve as cloud condensation nuclei and impact the global radiation balance (Cziczo et al., 2009; Ebert et al., 2011). Pb enters the atmosphere through emissions from natural and anthropogenic sources (Flament et al., 2011). Anthropogenic Pb emission sources are at least 1–2 orders of magnitude higher than natural emission sources (Komárek et al., 2008). In the United States, airborne Pb has decreased by a factor of 20 or more since the 1980 elimination of leaded gasoline (U.S. EPA, 2002), which was, historically, a major Pb 54

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aerodynamic size. The velocities of individual particles are subsequently determined by two continuous Nd:YAG diode laser beams (532 nm), scattered light from which is detected by a photomultiplier. Particle are ionized at the center of the ion source by a pulsed Nd:YAG laser (266 nm) to produce positive and negative ions, which are analyzed simultaneously by the SPAMS. Standard polystyrene latex spheres of known sizes are used to calibrate the detected particle sizes.

China and is experiencing extremely rapid economic expansion. In the past few decades, Guangzhou has suffered from severe air quality deterioration. The yearly atmospheric deposition of Pb (12.7 ± 6.72 mg/ m2) in the Pearl River Delta (PRD) is significantly elevated compared with that in other regions (Wong et al., 2003); the 2010 concentration of atmospheric Pb in Guangzhou was 417 ng/m3, while the yearly average Pb concentration measured only 261.0 ± 275.7 ng/m3 in over forty other major Chinese cities after 2000 (Duan and Tan, 2013). Atmospheric Pb has been shown to arise primarily from local emissions (Lee et al., 2007), but LCP sources in Guangzhou remain poorly understood overall. Thus, the contributions of various anthropogenic Pb sources must be quantified to better control LCP emissions. Traditional “offline” filter-based Pb isotopic ratio fingerprinting techniques have been widely used for LCP source apportionment (Cao et al., 2014; Widory et al., 2004; Zhao et al., 2015). Although these offline analyses can provide the average particle chemical composition over a period of time (Dall’Osto et al., 2010), they cannot determine the mixing state of Pb with other chemical species (Whiteaker et al., 2002). It is critical to understand the chemical composition and mixing state of LCPs, as these characteristics control the solubility and hydrophobicity of airborne particles (Gysel et al., 2007; Yeung et al., 2014). For instance, the presence of nitrate and sulfate in the particle phase generally enhances particle hygroscopicity. Further, the size of an LCP coated with soluble ions, which is controlled by hygroscopic growth (Vu et al., 2015; Zhou et al., 2001), influences the atmospheric fate of the particle (Utsunomiya et al., 2004). Single particle aerosol mass spectrometry (SPAMS) can simultaneously determine the aerodynamic size distribution and chemical characteristics of particles, including the particle mixing state (Gard et al., 1997; Laskin et al., 2012; Hinz and Spengler, 2007; Li et al., 2011). Moffet et al. characterized aerosols containing Zn, Pb, and Cl from an industrial region in Mexico City (Moffet et al., 2008a); they found that the particles in Mexico City generally contained internally mixed Zn, Pb, Cl, and P, which were originated primarily from industrial incineration. LCPs in Beijing, Shanghai, and Xiamen under various conditions have been studied and the possible LCP sources were deduced (Ma et al., 2016a; Zhang et al., 2009; Zhao et al., 2017). The SPAMS measurements were performed in Guangzhou during wintertime, from December 2, 2014 to January 3, 2015. The chemical composition and mixing state of airborne LCPs were explored under different ambient conditions to investigate the impact of meteorological conditions on LCPs, and LCP source apportionment was explored by comparing the observations with offline measurements of specific sources, including waste incineration, coal combustion, heavy diesel vehicle exhaust, industrial and mechanical processes, and dust.

2.3. Online LCP sampling The SPAMS was located on the roof of a two-floor building (~ 5 m above ground level). The online atmospheric particle measurement campaign spanned from December 2, 2014 to January 3, 2015. A PM2.5 cyclone (URG Corp., USA) was installed at the inlet of the SPAMS to exclude coarse particles. Nitrogen oxide (NOx), sulfur dioxide (SO2), ozone (O3), and PM2.5 were also measured. The mass concentrations of sulfate, nitrate, and hydrocarbon-like organic aerosol (HOA) in NR-PM1 (non-refractory components in PM with diameters of < 1 µm) were measured with a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS, Aerodyne Research Inc., Billerica, MA, USA); the HR-ToF-AMS results are explored in depth elsewhere (Qin et al., 2017). 2.4. Offline Pb source sampling The SPAMS was also used to analyze LCPs in source samples from waste incineration, coal combustion, heavy diesel vehicle exhaust, industrial and mechanical processes, and dust. Direct diesel vehicle exhaust sampling was performed on site as follows. Vehicle exhaust was sampled through a stainless steel tube inserted into the exhaust pipe of the vehicle, which was connected to a subsequent silica gel drier. The vehicle was started and idled for two minutes; then, a 0.5 m conductive silicone tube was used to connect the air drier tube to the SPAMS inlet. When the engine speed was stable at ca. 2000–3000 rpm, the exhaust was analyzed by the SPAMS. Coal combustion and waste incineration source samples were acquired through offline smoke particle collection. Source samples for industrial process, such as cement production, glass production, and building ceramics manufacturing, were also acquired offline by collecting related industrial exhaust in evacuated cylinders. For each source, three samples were collected continuously with vacuum bottles and bags, and subsequently analyzed directly using the SPAMS. In addition, 500 g each of fuel and dust were collected from the dust removal equipment and stored in self-sealing bags as auxiliary samples. The dust sources evaluated herein include road and soil dust. Soil dust was collected from depths ranging from 0 to 30 cm below ground. Road dust samples were acquired by sweeping dust from major roads. During each sample collection period, three samples (of ~200 g each) were collected consecutively from parallel areas and stored in self-sealing bags. The samples were then sifted through a 150-mesh sieve to obtain particles with diameters of < 100 µm. After screening, the samples were dried naturally, and approximately 10 g of each soil sample was placed in a glass sampling bottle. An air filter was attached to the inlet valve on the glass container and the particle samples were transferred to the SPAMS through an outlet valve and a copper transfer line. The filter allowed particle-free air to flow through the container, entraining a consistent flow of soil-laden air into the SPAMS. For all offline source sample types, our results are consistent with previous studies on similar sources, including automobile exhaust (Silva and Prather, 1997; Toner et al., 2006), soil dust (Silva et al., 2000), and biomass burning (Silva et al., 1999).

2. Materials and methods 2.1. Sampling site The field campaign was conducted at the China Meteorological Administration (CMA) Atmospheric Watch Network station (23°00′ N, 113°11′ E) (Fig. 1) in the Panyu district in Guangzhou, China (Fig. S1). The station is operated by the CMA Institute of Tropical and Marine Meteorology (ITMM) and surrounded by residential neighborhoods; there are no significant pollution sources nearby. More information on this site is available elsewhere (Tan et al., 2013; Cheung et al., 2016). 2.2. SPAMS Details regarding the SPAMS (Hexin Analytical Instrument Co., Ltd., China) have been reported by Li et al. (2011). In short, air is introduced into an interior vacuum through a critical orifice. An auxiliary pump is used to shorten the particle residence time in the sampling tube. The particles are then gradually focused onto the axis of the aerodynamic lens, where they are accelerated to given velocities depending on their

2.5. SPAMS data analysis Positive and negative ion mass spectra were acquired for 4,236,115 particles, which accounted for approximately 33% of the total sized particles. In order to minimize background noise interference, LCPs 55

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were defined as those particles with spectra containing 206Pb, 207Pb, and/or 208Pb peak areas greater than 50 (Ma et al., 2016a). As a result, 184,271 LCPs were identified. All LCP mass spectra were converted to lists of peaks at each m/z, which were imported into YADDA, a MATLAB (MathWorks, Inc.)-based software toolkit (http://www.yaada. org/), and further classified with an adaptive resonance theory (ART2a)-based neural network algorithm (Song et al., 1999) with a vigilance factor of 0.85, a learning rate of 0.05, and a maximum of 20 iterations; this data analysis method was also used to analyze mass spectra from the Pb source particles collected offline.

The average mass spectra are displayed in Fig. 1 for major LCP types. Identification of the most probable ions corresponding to a given peak was based on previous laboratory and field studies (Gard et al., 1998; Liu et al., 1997; Noble and Prather, 1998). Specific LCP ion fragments can be used as markers to classify distinct particle types (Whiteaker et al., 2002). Chloride is present in most LCP types, likely due to the wide variety of atmospheric chloride sources, which include sea salt (Keene et al., 1990), volcanic emissions (Symonds et al., 1988), marine biological processes (Wuosmaa and Hager, 1990), fossil fuel combustion (Block and Dams, 1975), and waste incineration (Keane, 2007; Uchida et al., 1988). As seen in Fig. 1a-c and e, the mass spectra all include positive 23 Na+, 39K+, and 63/65Cu+ peaks and negative 35/37Cl-, 46NO2- and 62 NO3-, 97HSO4-, and 79PO3- peaks. The maximum Pb peak intensity is found in Pb-Cl particles (Fig. 1a). Pb-Cl-EC particles (Fig. 1b) are typified by peaks at m/z ± 12 n (n = 1, 2, 3…) and a strong negative 97 HSO4- peak. Pb-Cl-Fe particles (Fig. 1c) are characterized by 54/56Fe+ peaks. Pb-Cl-Li particles (Fig. 1d) exhibit spectral variation with strong 7 + 35/37 Li , Cl , O-/ OH-, and CN- peaks and a lack of 97HSO4-. Pb-Cl-Li particles were probably derived from coal fly ash (Liu et al., 1997; Furutani et al., 2011; Guazzotti et al., 2003), as evidenced by 7Li+ peak. The presence of 16O- and 17OH- reflects high particle water content (Dall’Osto et al., 2004), probably in the form of hydrates. The Pb-ClAlSi particle mass spectrum (Fig. 1e) is characterized by 27Al+, 40Ca+, 56 CaO+/Fe+, 60SiO2-, and 76SiO3- peaks, suggesting an association with mineral dust (Moffet et al., 2008b). Fig. 1f-h show mass spectra with positive 23Na+ and 39K+ peaks and negative 46NO2-, 62NO3-, 97HSO4-, and 79PO3- peaks; 35/37Cl- peaks can be seen in Fig. 1f and h. Pb-Cl-Zn particles (Fig. 1f) were likely derived from industrial processes, as evidenced by the isotopic Zn peaks at m/zs 64 and 66, which have also been detected in industrial regions in Mexico City and the United States (Gysel et al., 2007). Notably, the nitrate peaks are the most intense ion peaks for all particle types except Pb-Cl-Li, which is logical as 62NO3- is a dominant secondary species for most pollution sources (Shields, 2008). Intense nitrate and sulfate peaks also suggest advanced particle aging. Pb-Cl-OC particles (Fig. 1h) are differentiated by the presence of C3H+, C2HO+, and C3H7+ peaks. Cucontaining particles are identified based on whether the isotopic Cu+ peaks at m/zs 63 and 65 meet the following peak area ratio criteria: 1) m/zs 51:63 < 1, 2) 43:63 < 1, and 3) 74:65 < 1. Only Pb-Cl-Zn, PbSec, and Pb-Cl-OC particles do not contain Cu (Fig. 1g-h). This co-occurrence of Cu and Pb differs greatly from the LCP composition founds in industrial regions in Mexico City and United States, where LCPs are predominantly internally mixed with Zn (Murphy et al., 2007; Shields, 2008).

3. Results and discussion 3.1. Meteorological observations Temporal variations in meteorological values, including wind speed, wind direction, temperature, and relative humidity (RH); NOx, SO2, O3, and PM2.5 concentrations; and LCP counts and number fractions (NFs) are shown at 3 h temporal resolution in Fig. S2. The LCP NF was defined as the percent ratio of the number of LCPs to the total particle number. The NF varies from 0.34% to 24.55% during the campaign, consistent with LCP NF values (3.2–22.7%) measured in Beijing under various weather conditions (Ma et al., 2016b). Herein, transient spikes in LCP number may indicate the impact of point source plumes (Snyder et al., 2009). In addition, the average LCP number fraction (APF), which equals 4.35%, is similar to that from the CLACE 5 campaign at the Jungfraujoch Research Station (Murphy et al., 2007). The varying weather conditions throughout the campaign (Fig. S2a) led to variations in particle number. Periods with LCP NFs of more than three times the APF were defined as high LCP NF periods (HLFPs); three HLFPs were identified (Fig. S2b), namely H1 (08:00 December 5–04:00 December 9), H3 (04:00 December 18–04:00 December 19), and H5 (19:00 December 31–22:00 January 2). Conversely, periods with LCP NF below the APF were defined as low LCP NF periods (LLFPs); two LLFPs were identified, including L2 (01:00 December 10–00:00 December 13) and L4 (00:00 December 24–08:00 December 30). Air mass back trajectories for these five high- and low- LCP periods are presented in Fig. S3. Air masses from northeastern Guangzhou were dominant during H1, L2, and H5 and may have transported air pollutants from other parts of China to Guangzhou. During H3 and L4, the air masses originated partially over the ocean were clean, and likely played a role in reducing local air pollution. HLFPs were also associated with higher PM2.5. 3.2. LCP classification

3.3. LCP temporal characteristics

Of a total of 523 particle clusters yielded by ART-2a, 97% were manually classified into eight major particle types, namely Pb-Cl, Pb-ClEC (Elemental Carbon), Pb-Cl-Fe, Pb-Cl-Li, Pb-Cl-AlSi, Pb-Cl-OC (Organic Carbon), Pb-Sec (Secondary species), and Pb-Cl-Zn. Pb-Cl (67.1%) and Pb-Cl-Zn (0.5%) contribute the highest and lowest numbers of particles, respectively (Table 1).

3.3.1. Temporal variations in LCPs Local stand time is used herein. High NFs of a given LCP type (Fig. S4) may indicate the impact of a specific source. For instance, Pb-Sec particle NFs are significantly higher during LLFPs (L2, L4). During L2, PM2.5 concentrations ranged from 30.7 to 88.0 μg/m3 (average 57.2 μg/ m3), while during L4, PM2.5 concentrations range from 29.9 to 166.5 μg/m3 (average 82.2 μg/m3) (Fig. S2a). Higher proportions of nitrate and sulfate in PM2.5 indicate secondary particle processing during L2 and L4, according to previous studies in Guangzhou showing that the amount of secondary inorganic species can indicate the degree of PM2.5 aging (Huang et al., 2014).

Table 1 Number fractions (of the total particle number) of major LCP types. Primary LCP type

LCP fraction

Pb-Cl Pb-Cl-Fe Pb-Sec Pb-Cl-EC Pb-Cl-OC Pb-Cl-Li Pb-Cl-AlSi Pb-Cl-Zn

67.1% 12.6% 7.7% 6.4% 3.4% 1.2% 1.1% 0.5%

3.3.2. LCP diurnal patterns Diurnal patterns (3 h resolution) are shown in Fig. 2 for HLFPs and LLFPs. Pb-Cl-EC and Pb-Cl-OC particles have almost identical diurnal patterns, likely because they are both emitted primarily by local heavy duty diesel trucks. Pb-Cl-EC particles peak at 21:00 during LLFPs and 00:00 during HLFPs and decrease between 03:00 and 9:00, consistent 56

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Fig. 2. Diurnal hourly averages of major LCP types, NOx and O3 mass concentrations, RH, and temperature. The dotted and solid lines represent average diurnal patterns during LLFPs (L2 and L4) and HLFPs (H1, H3, and H5), respectively.

during HLFPs. During HLFPs, the O3 diurnal pattern is consistent with the Pb-Sec profile before 18:00, which indicates that NOx and SO2 may be rapidly oxidized by O3 accumulated throughout the day to form nitrate and sulfate. The Pb-Sec fraction remains high from 18:00–21:00, possibly due to higher nighttime RH. During LLFPs, the Pb-Sec concentration is lowest at 12:00, likely in response to decreased RH, suggesting that RH controls the formation of nitrate and sulfate from NOx and SO2. During LLFPs, the inverse average Pb-Cl and Pb-Sec diurnal patterns suggest the replacement of Cl in primary LCP particles by secondary inorganic species such as nitrate (Gysel et al., 2007). The PbCl-AlSi particle NFs increase between 03:00 and 18:00 during LLFPs and between 12:00 and 18:00 during HLFPs, respectively, which may be caused by differences in re-suspended dust. Pb-Cl-Fe particles have

with heavy duty diesel truck emissions previously measured in Guangzhou, which peak at midnight and decrease during daytime (Yu et al., 2014); this pattern can also be seen in HR-ToF-AMS data, which show nighttime increases in traffic-related HOA (Fig. S5) (Qin et al., 2017). The Pb-Cl particle diurnal pattern differs during LLFPs and HLFPs. LLFPs feature a maximum and minimum at 09:00 and 21:00, respectively, while HLFPs feature a maximum at 12:00 and two minimums at 06:00 and 18:00, indicating that Pb-Cl particles probably arose from two different local sources. Pb-Sec particle diurnal patterns also differ between LLFPs and HLFPs; HLFPs feature a maximum at 12:00 and a minimum at 18:00, and reach another maximum at 21:00, while LLFPs feature a minimum at 12:00 and a maximum at 21:00. The PbSec particle NF is approximately four times higher during LLFPs than 57

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Fig. 3. Mixing ratios of secondary inorganic species in various LCP types; the color scale represents the fraction of particles within the given LCP type (y-axis) that contains the given secondary species (x-axis).

supermicron dust particles (Sullivan et al., 2007), agreeable with the overwhelmingly submicron size distribution of Pb-Cl-AlSi particles. Aluminosilicates are commonly generated by mechanical processes (Murphy and Thomson, 1997) and exist generally in the coarse mode (Lee et al., 2003). However, fine-mode Pb-Cl-AlSi particles may be derived from re-suspended soil dust, which normally contains abundant NH4+ (Schlesinger and Hartley, 1992); thus, NH4+ may not always be indicative of aging.

similar diurnal patterns during HLFPs and LLFPs. Pb-Cl-Zn particles show decreasing trend and reach a minimum at 21:00 during HLFPs, whereas the particles show a rapid decrease between 3:00 and 6:00, then zigzag during LLFPs. Pb-Cl-Li Particles feature evening minimum during HLFPs and a maximum at 21:00 during LLFP. 3.4. Mixing states of secondary inorganic species in LCPs Most LCP types contain ammonium, nitrate, and sulfate peaks (Fig. 3), indicating secondary LCP processing during atmospheric transport, and also show distinct differences in chemical species as a result of internal mixing within a particle. In general, nitrate has a higher degree of mixing with Pb particles than do sulfate and ammonium. The nitrate and sulfate diurnal hourly average concentrations (Fig. S5) and average mixing ratios (Fig. 3) are higher during LLCPs than during HLCPs. Elevated NOx concentrations, lower temperatures, and higher RH conditions (Fig. S2a) may promote the formation of nitrate on LCPs (Wang et al., 2009). Additionally, average wind speeds are low during L2 (1.53 m/s) and L4 (0.89 m/s), providing stagnant conditions that may facilitate accumulation and aging. The SO2 and NOx concentrations peak in H5 (Fig. S2), but the low average RH (37.0%) during that time may have hindered the formation of sulfate and nitrate from SO2 and NOx. The average mixing ratios of ammonium are higher during H1 and H3 (69.7% and 71.8%, respectively) than during L2 and L4, which may have been caused by higher NH3 concentrations. Pb-Cl-Zn particles, which were probably freshly emitted by industrial processes, are strongly (100%) associated with nitrate. This strong association suggests that these particles underwent heterogeneous reaction with HNO3 (Gysel et al., 2007; Moffet et al., 2008b). Pb-Cl particles are also strongly associated with nitrate (100%), but associated less (~ 60% or less) with other species. Pb-Cl-EC and Pb-ClOC particles typically contain internally mixed nitrate (100%), sulfate, and ammonium. The formation of secondary inorganic species on carbonaceous particle surfaces may have been driven by high RH and low temperature near midnight. Pb-Cl-Li particles exhibit the least mixing with nitrate (18.1%) and sulfate (6.8%) and higher association with ammonium (56.7%), suggesting that Li mixed more easily with ammonia under the study conditions herein. Pb-Cl-AlSi particles probably arose from re-suspended dust and tended to mix with nitrate (100%), but only moderately with sulfate (42.6%). Nitrate tends to accumulate in submicron dust particles and sulfate tends to accumulate in

3.5. LCP source apportionment 3.5.1. Comparison of atmospheric LCPs with emission source LCPs Mass spectra from atmospheric LCPs were compared with those from authentic emission sources using the selection criteria mentioned in Section 2.4 in order to apportion LCPs to various sources in Guangzhou, including coal combustion, waste incineration, diesel vehicle exhaust, industrial processes, and dust. Correlations were examined between the relative peak areas at each m/z in the atmospheric LCP mass spectra and those in the emission source mass spectra. The mass spectral comparison of four LCP types with five emission sources is shown in Fig. 4. The average LCP mass spectra from coal combustion and waste incineration are similar to atmospheric Pb-Cl particle mass spectrum (Fig. 1a). LCPs from both emission sources and ambient particles contain 35/37Cl- and 63/65Cu+ peaks, suggesting that a significant fraction of Pb-Cl particles may have originated from coal combustion and/or waste incineration. Waste incineration is currently increasing rapidly in China, and Zhejiang, Guangdong, and Jiangsu provinces contained 57% of incineration plants in China at the end of 2010 (Tian et al., 2012a). Waste incineration can lead to the volatilization of Pb compounds, which then re-condense and enter the environment (Wey et al., 2001; Yao and Naruse, 2009; Wang et al., 2014). Although Pb-Cl particle mass spectra are similar to the waste incineration LCP mass spectra, their size distributions are different (Fig. S6). The size distribution of LCPs from waste incineration, which spans 0.4–2.0 µm, is broader than that of PbCl particles herein, likely due to enhanced processing of the atmospheric particles. Numerous types of coal are used for industrial and civilian purposes in China. The coal chlorine concentration averages ~ 0.1% by weight (Block and Dams, 1975), and chlorine is liberated as HCl when the coal is burned (Graedel and Keene, 1995). The Pb content of Chinese coal is ~ 13 μg/g (Fang et al., 2014), and total emissions of Pb due to coal 58

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Fig. 4. Relative average mass spectral signal intensities from various emission sources and LCP types. The insets show lithium signatures from waste incineration and coal combustion and zinc signatures from industrial process emissions. The panels on the right show Pearson's correlations between LCP types and Pb emission source mass spectra. Positive and negative mass spectral data points are shown in orange and dark green, respectively.

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Fig. 5. LCP source apportionment during each period. The colors correspond to the sources named at the top of the figure; the numbers represent the percentage of particles contributed by a given source.

fluorescence and neutron activation analysis (Murphy and Thomson, 1997). Li has been found in Chinese coals at a concentration of 32 μg/g (Dai et al., 2012) and is released into the raw gas during waste incineration (Belevi and Moench, 2000). The size distribution of Pb-Cl-Li particles is similar to that of coal combustion particles (Fig. S6). Thus, coal combustion and waste incineration are quite likely the main sources of Pb-Cl and Pb-Cl-Li. The industrial particle positive mass spectrum features isotopic Zn peaks at m/zs 64 and 66 and a chemical composition similar to that observed in Pb-Cl-Zn particles (Fig. 1). The industrial process LCPs are unimodally distributed with a mode at 0.5 µm, while Pb-Cl-Zn particles are larger, with a size distribution maximum at 0.8 µm (Fig. S6); this may be explained by aging after emission, which generally leads to upwards shifts in the size distribution. Previous work in an industrial region in Mexico City has shown internal mixing of Pb with Zn and Cl (Gysel et al., 2007)；thus, Pb-Cl-Zn particles may have arisen from industrial sources. SiO2-, SiO3-, and Al+ are commonly used as dust markers (Dall’Osto et al., 2010). Pb and Ca are often detected in road dust as well (Murphy and Thomson, 1997). Re-suspended soil has been found to be a significant source of airborne Pb near highways and industrial facilities (Young et al., 2002). Herein, SiO2-, SiO3-, and Al+ are detected in both the dust source and Pb-Cl-AlSi particles, suggesting that dust may have been the primary source of Pb-Cl-AlSi particles. LCPs from the dust source feature a unimodal distribution similar to that of Pb-Cl-AlSi particles (Fig. S6), but broader. Thus, Pb-Cl-AlSi particles were probably derived from industrial processes, crustal sources, and re-suspended dust particles containing Pb deposited previously, when leaded gasoline was still in use. Iron and steel industrial activities, dust, and combustion fly ash are likely the main sources of Fe-containing aerosols in Shanghai (Zhang et al., 2014), while the iron in LCPs in Beijing may arise from industrial processes (Ma et al., 2016b). Furthermore, iron is not a major component of crustal matter (McLennan, 2001), and dust storms also do not exhibit enhanced Fe levels, relative to their source regions (Chuang et al., 2005). Hence, Pb-Cl-Fe particles herein may have arisen mainly from iron- and steel-related industrial activities. The presence of secondary inorganic species in Pb-Sec particles indicates that these particles were the products of heterogeneous aging reactions. Note that particulate Cl- can be replaced by NO3- (Widory

combustion have increased rapidly in China, from 2671.73 t in 1980 to 12,561.77 t in 2008 or a rate of 5.7%/year (Tian et al., 2012b). In some parts of China, such as Shanghai and Xiamen, coal combustion has become the major source of ambient Pb since the regulation of leaded gasoline (Chen et al., 2005; Zhu et al., 2010). In Guangzhou, coal combustion, industrial processes, and re-suspended particles deposited from previous leaded gasoline vehicle exhaust constituted the major sources of atmospheric Pb in 2003 (Duzgoren-Aydin, 2007). Herein, PbCl particles and LCPs from coal combustion have similar unimodal size distributions spanning 0.5–0.9 µm (Fig. S6), suggesting potential Pb-Cl particle contribution from coal combustion. The heavy duty diesel truck exhaust mass spectrum (Fig. 4) is very similar to that for Pb-Cl-EC particles, which features m/z ± 12 n (n = 1, 2, 3…) carbon clusters and weak OC fragment peaks at 27 C2H3+, 37C3H+, and 43C3H7+, as well as a 79PO3- peak. Phosphate is present in exhaust particles due to an engine oil additive that functions as an anti-wear agent (Gautam et al., 1999). LCPs associated with PO3and PO4- from the phosphate industry have been detected only in Shanghai (Zhang et al., 2009); Beijing (Ma et al., 2016a) and Guangzhou lack phosphate industries. The diesel truck exhaust and PbCl-EC particle mass spectra are the most highly correlated, their positive and negative mass spectra correlations are 0.99, 0.91, respectively. Vehicular combustion processes produce EC-containing LCPs that are often coated with semi-volatile organic carbon species (Amann and Siegla, 1981). The diurnal patterns of Pb-Cl-EC and Pb-Cl-OC particle NFs and traffic-related HOA concentrations vary with diesel truck emissions, which generally peak at midnight and are low during the daytime in Guangzhou. In addition, Pb-Cl-EC particle size distribution is similar to that of the diesel vehicle exhaust LCPs (Fig. S6), suggesting closely connected Pb-Cl-EC particle and diesel vehicle exhaust sources. Hence, we can assume that EC, along with OC, originated primarily from heavy duty diesel trucks, but also from coal combustion; previous source characterization studies have also asserted that OC and associated EC are derived from heavy duty diesel truck exhaust (Toner et al., 2006; Sodeman et al., 2005). Although leaded gasoline has been regulated, Pb emissions remain possible from residual fuel oil, crude oil, brake linings, and tires (Murphy et al., 2007; Hjortenkrans et al., 2007; Dall’Osto et al., 2014). The detection of Li is noteworthy, as Li cannot be detected using typical particulate matter chemical analysis methods, such as X-ray 60

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201506010013); the Science Technology and Innovation Committee of Shenzhen Municipality (Grant no. JCYJ20160401095857424); and the Guangzhou Industry University Research Collaborative Innovation Major Project (Grant no. 2016201604030082). The authors would like to thank the editors and reviewers for their valuable comments.

et al., 2004) via:

MCln (s) + nHNO3(g ) → M (NO3)n (s) + nHCl (g )

(R1)

where M represents Pb, Zn, or Na. 3.5.2. LCP source apportionment Fig. 5 shows the LCP source apportionment derived from the discussion in Section 3.5.1. Coal combustion and waste incineration are dominant sources, accounting for more than 60% of the total LCP number. However, the LCP source profiles vary substantially throughout the campaign. The coal combustion and waste incineration NFs vary little during HLFPs; however, the contributions of coal combustion and waste incineration, which average 81.9% during HLFPs, decrease distinctly to 68.1% during LLFPs. The secondary LCP NF is more than four times higher during LLFPs than during HLFPs. Diesel truck emissions are about three times higher during HLFPs than during LLFPs, during which they average 13.7% and 4.7%, respectively; thus, diesel truck emissions play a more significant role during HLFPs. Following coal combustion and waste incineration, steel- and iron-related sources are the second-largest LCP contributors throughout the campaign. Average LCP NFs from steel and iron sources vary between 6.6% and 9.6% during HLFPs and decrease to 4.7–8.0% during LLFPs.

Appendix A. Supporting information Supplementary data associated with this article can be found in the online version at doi:10.1016/j.ecoenv.2018.10.006 References Amann, C.A., Siegla, D.C., 1981. Diesel particulates-what they are and why. Aerosol Sci. Technol. 1, 73–101. Barregard, L., Fabricius-Lagging, E., Lundh, T., Molne, J., Wallin, M., Olausson, M., Modigh, C., Sallsten, G., 2010. Cadmium, mercury, and lead in kidney cortex of living kidney donors: impact of different exposure sources. Environ. Res. 110, 47–54. Belevi, H., Moench, H., 2000. Factors determining the element behavior in municipal solid waste incinerators. 1. Field Stud. Environ. Sci. Technol. 34, 2501–2506. Block, C., Dams, R., 1975. Inorganic composition of Belgian coals and coal ashes. Environ. Sci. Technol. 9, 146–150. Cai, J., Wang, J., Zhang, Y., Tian, H., Zhu, C., Gross, D.S., Hu, M., Hao, J., He, K., Wang, S., Zheng, M., 2017. Source apportionment of Pb-containing particles in Beijing during January. Environ. Pollut. 226, 30–40. Cao, S., Duan, X., Zhao, X., Wang, B., Ma, J., Fan, D., Sun, C., He, B., Wei, F., Jiang, G., 2014. Isotopic ratio based source apportionment of children's blood lead around coking plant area. Environ. Int. 73, 158–166. Chen, J., Tan, M., Li, Y., Zhang, Y., Lu, W., Tong, Y., Zhang, G., Li, Y., 2005. A lead isotope record of Shanghai atmospheric lead emissions in total suspended particles during the period of phasing out of leaded gasoline. Atmos. Environ. 39, 1245–1253. Cheung, H.H.Y., Tan, H., Xu, H., Li, F., Wu, C., Yu, J.Z., Chan, C.K., 2016. Measurements of non-volatile aerosols with a VTDMA and their correlations with carbonaceous aerosols in Guangzhou, China. Atmos. Chem. Phys. 16, 8431–8446. Cho, S.-H., Richmond-Bryant, J., Thornburg, J., Portzer, J., Vanderpool, R., Cavender, K., Rice, J., 2011. A literature review of concentrations and size distributions of ambient airborne Pb-containing particulate matter. Atmos. Environ. 45, 5005–5015. Chuang, P., Duvall, R., Shafer, M., Schauer, J., 2005. The origin of water soluble particulate iron in the Asian atmospheric outflow. Geophys. Res. Lett. 32. https://doi.org/ 10.1029/2004GL021946. Csavina, J., Taylor, M.P., Félix, O., Rine, K.P., Sáez, A.E., Betterton, E.A., 2014. Sizeresolved dust and aerosol contaminants associated with copper and lead smelting emissions: implications for emission management and human health. Sci. Total Environ. 493, 750–756. Cziczo, D.J., Stetzer, O., Worringen, A., Ebert, M., Weinbruch, S., Kamphus, M., Gallavardin, S.J., Curtius, J., Borrmann, S., Froyd, K.D., 2009. Inadvertent climate modification due to anthropogenic lead. Nat. Geosci. 2, 333–336. Dai, S., Ren, D., Chou, C.-L., Finkelman, R.B., Seredin, V.V., Zhou, Y., 2012. Geochemistry of trace elements in Chinese coals: a review of abundances, genetic types, impacts on human health, and industrial utilization. Int. J. Coal Geol. 94, 3–21. Daland Juberg, R., Cindy, F., Kleiman, M.P.H., Simona, C., Kwon, M.P.H., 1997. Position paper of the American council on science and health: lead and human health. Ecotoxicol. Environ. Saf. 38, 162–180. Dall’Osto, M., Beddows, D., Kinnersley, R.P., Harrison, R.M., Donovan, R.J., Heal, M.R., 2004. Characterization of individual airborne particles by using aerosol time-of-flight mass spectrometry at Mace Head, Ireland. J. Geophys. Res.-Atmos. 109. https://doi. org/10.1029/2004JD004747. Dall’Osto, M., Harrison, R.M., Highwood, E.J., O’Dowd, C., Ceburnis, D., Querol, X., Achterberg, E.P., 2010. Variation of the mixing state of Saharan dust particles with atmospheric transport. Atmos. Environ. 44, 3135–3146. Dall’Osto, M., Beddows, D.C., Gietl, J.K., Olatunbosun, O.A., Yang, X., Harrison, R.M., 2014. Characteristics of tyre dust in polluted air: studies by single particle mass spectrometry (ATOFMS). Atmos. Environ. 94, 224–230. Duan, J., Tan, J., 2013. Atmospheric heavy metals and Arsenic in China: situation, sources and control policies. Atmos. Environ. 74, 93–101. Duzgoren-Aydin, N.S., 2007. Sources and characteristics of lead pollution in the urban environment of Guangzhou. Sci. Total Environ. 385, 182–195. Ebert, M., Worringen, A., Benker, N., Mertes, S., Weingartner, E., Weinbruch, S., 2011. Chemical composition and mixing-state of ice residuals sampled within mixed phase clouds. Atmos. Chem. Phys. 11, 2805–2816. Fang, T., Liu, G., Zhou, C., Sun, R., Chen, J., Wu, D., 2014. Lead in Chinese coals: distribution, modes of occurrence, and environmental effects. Environ. Geochem. Health 36, 563–581. Flament, P., Bertho, M.L., Deboudt, K., Veron, A., Puskaric, E., 2011. European isotopic signatures for lead in atmospheric aerosols: a source apportionment based upon 206Pb/207Pb ratios. Sci. Total Environ. 296, 35–57. Furutani, H., Jung, J., Miura, K., Takami, A., Kato, S., Kajii, Y., Uematsu, M., 2011. Singleparticle chemical characterization and source apportionment of iron-containing atmospheric aerosols in Asian outflow. J. Geophys. Res.-Atmos. 116. https://doi.org/ 10.1029/2011JD015867. Gard, E., Mayer, J.E., Morrical, B.D., Dienes, T., Fergenson, D.P., Prather, K.A., 1997. Real time analysis of individual atmospheric aerosol particles: design and performance of

4. Conclusions The SPAMS was used to characterize LCPs in Guangzhou during wintertime. Based on particle mass spectral features, LCPs were clustered into eight major types: Pb-Cl, Pb-Cl-EC, Pb-Cl-Fe, Pb-Cl-Li, Pb-ClAlSi, Pb-Cl-OC, Pb-Sec, and Pb-Cl-Zn. Pb-Cl particles constituted over 67% of LCPs. Periods with LCP number fractions greater than three times the APF (4.35%) and below the APF were defined as high LCP number fraction periods (HLFPs: H1, H3, and H5) and low LCP number fraction periods (LLFPs: L2 and L4), respectively; LCPs were examined in depth during these periods. Pb-Cl and Pb-Sec particles exhibit different diurnal patterns during HLFPs and LLFPs; the inverse Pb-Cl and Pb-Sec particle diurnal trends during LLFPs suggest that Cl in Pb-Cl particles was replaced by secondary inorganic species. The Pb-Sec particle NF is about four times greater during LLFPs than during HLFPs. The LLFP Pb-Sec diurnal patterns are consistent with that of RH, while the HLFP Pb-Sec diurnal pattern is more similar to that of O3, indicating that during LLFPs and HLFPs, heterogeneous reactions and photochemical activities, respectively, controlled the formation of nitrate and sulfate from NOx and SO2. Source apportionment was performed by comparing atmospheric LCP mass spectra with mass spectra of authentic Pb emission sources, including coal combustion, waste incineration, diesel vehicle exhaust, industrial processes, and dust. Averaged over the five periods, ~76% of LCPs arose from coal combustion and/or waste incineration, which were the dominant sources during all five periods, followed by diesel trucks during LLFPs and ironand steel-related sources during HLFPs; HLFP LCPs arose mainly from primary emissions. These results can be used to more efficiently control Pb emission sources and prevent harm to human health. Acknowledgements This work was supported by the National Natural Science Foundation of China (Grant no. 21607056); the State Key Laboratory of Organic Geochemistry, GIGCAS (Grant no. SKLOG-2016); the National Key Technology R&D Program (Grant no. 2014BAC21B01); the National Research Program for Key Issues in Air Pollution Control (Grant no. DQGG0107); the Guangdong Province Public Interest Research and Capacity Building Special Fund (Grant no. 2014B020216005); the Fundamental Research Funds for the Central Universities (Grant no. 21617455); the Guangdong Applied Science and Technology Research and Development (Grant no. 2015B020236003); the Pearl River Nova Program of Guangzhou (Grant no. 61

Ecotoxicology and Environmental Safety 168 (2019) 53–63

J. Lu et al.

A., Reinard, M., Thomson, D., Thornberry, T., 2007. Distribution of lead in single atmospheric particles. Atmos. Chem. Phys. 7, 3195–3210. Nevin, R., 2000. How lead exposure relates to temporal changes in IQ, violent crime, and unwed pregnancy. Environ. Res. 83, 1–22. Noble, C.A., Prather, K.A., 1998. Aerosol time-of-flight mass spectrometry: a new method for performing real-time characterization of aerosol particles. Appl. Occup. Environ. Hyg. 13, 439–443. Qin, Y.M., Tan, H.B., Li, Y.J., Schurman, M.I., Li, F., Canonaco, F., Prévôt, A.S.H., Chan, C.K., 2017. Impacts of traffic emissions on atmospheric particulate nitrate and organics at a downwind site on the periphery of Guangzhou, China. Atmos. Chem. Phys. 17, 10245–10258. Roper, W.L., Houk, V., Falk, H., Binder, S., 1991. Preventing Lead Poisoning in Young Children: A Statement by the Centers for Disease Control, October 1991. Centers for Disease Control, Atlanta, GA (United States). Schlesinger, W.H., Hartley, A.E., 1992. A global budget for atmospheric NH3. Biogeochemistry 15, 191–211. Shields, L.G., 2008. Single Particle Characterization, Source Apportionment, and Aging Effects of Ambient Aerosols in Southern California (Ph.D., UC San Diego). University of California, San Diego. Silva, P.J., Prather, K.A., 1997. On-line characterization of individual particles from automobile emissions. Environ. Sci. Technol. 31, 3074–3080. Silva, P.J., Liu, D.Y., Noble, C.A., Prather, K.A., 1999. Size and chemical characterization of individual particles resulting from biomass burning of local Southern California species. Environ. Sci. Technol. 33, 3068–3076. Silva, P.J., Carlin, R.A., Prather, K.A., 2000. Single particle analysis of suspended soil dust from Southern California. Atmos. Environ. 34, 1811–1820. Snyder, D.C., Schauer, J.J., Gross, D.S., Turner, J.R., 2009. Estimating the contribution of point sources to atmospheric metals using single-particle mass spectrometry. Atmos. Environ. 43, 4033–4042. Sodeman, D.A., Toner, S.M., Prather, K.A., 2005. Determination of single particle mass spectral signatures from light-duty vehicle emissions. Environ. Sci. Technol. 39, 4569–4580. Song, X.-H., Hopke, P.K., Fergenson, D.P., Prather, K.A., 1999. Classification of single particles analyzed by ATOFMS using an artificial neural network, ART-2A. Anal. Chem. 71, 860–865. Sullivan, R., Guazzotti, S., Sodeman, D., Prather, K.A., 2007. Direct observations of the atmospheric processing of Asian mineral dust. Atmos. Chem. Phys. 7, 1213–1236. Sun, Y., Zhuang, G., Zhang, W., Wang, Y., Zhuang, Y., 2006. Characteristics and sources of lead pollution after phasing out leaded gasoline in Beijing. Atmos. Environ. 40, 2973–2985. Symonds, R.B., Rose, W.I., Reed, M.H., 1988. Contribution of C1-and F-bearing gases to the atmosphere by volcanoes. Nature 334, 415–418. Tan, H., Yin, Y., Gu, X., Li, F., Chan, P.W., Xu, H., Deng, X., Wan, Q., 2013. An observational study of the hygroscopic properties of aerosols over the Pearl River Delta region. Atmos. Environ. 77, 817–826. Tian, H., Gao, H.,J., Lu, L., Zhao, D., Cheng, K., Qiu, P., 2012a. Temporal trends and spatial variation characteristics of hazardous air pollutant emission inventory from municipal solid waste incineration in China. Environ. Sci. Technol. 46, 10364–10371. Tian, H., Cheng, K., Wang, Y., Zhao, D., Lu, L., Jia, W., Hao, J., 2012b. Temporal and spatial variation characteristics of atmospheric emissions of Cd, Cr, and Pb from coal in China. Atmos. Environ. 50, 157–163. Toner, S.M., Sodeman, D.A., Prather, K.A., 2006. Single particle characterization of ultrafine and accumulation mode particles from heavy duty diesel vehicles using aerosol time-of-flight mass spectrometry. Environ. Sci. Technol. 40, 3912–3921. U.S. EPA, 2002. (U.S. Environmental Protection Agency). Latest Findings on National Air Quality: 2001 Status and Trends. Available: 〈https://www.epa.gov/air-trends/leadtrends〉. Uchida, S., Kamo, H., Kubota, H., 1988. The source of hydrogen chloride emission from municipal refuse incinerators. Ind. Eng. Chem. Res. 27, 2188–2190. Utsunomiya, S., Jensen, K.A., Keeler, G.J., Ewing, R.C., 2004. Direct identification of trace metals in fine and ultrafine particles in the Detroit urban atmosphere. Environ. Sci. Technol. 38, 2289–2297. Vu, T.V., Delgado-Saborit, J.M., Harrison, R.M., 2015. A review of hygroscopic growth factors of submicron aerosols from different sources and its implication for calculation of lung deposition efficiency of ambient aerosols. Air Qual. Atmos. Hlth. 8, 429–440. Wang, S.-J., Zhang, H., Shao, L.-M., Liu, S.-M., He, P.-J., 2014. Thermochemical reaction mechanism of lead oxide with poly (vinyl chloride) in waste thermal treatment. Chemosphere 117, 353–359. Wang, X., Zhang, Y., Chen, H., Yang, X., Chen, J., Geng, F., 2009. Particulate nitrate formation in a highly polluted urban area: a case study by single-particle mass spectrometry in Shanghai. Environ. Sci. Technol. 43, 3061–3066. Wang, Y.L., 1984. Industrial lead posioning in China over the past 33 years. Ecotoxicol. Environ. Saf. 8, 526–530. Wey, M.-Y., Ou, W.-Y., Liu, Z.-S., Tseng, H.-H., Yang, W.-Y., Chiang, B.-C., 2001. Pollutants in incineration flue gas. J. Hazard. Mater. 82, 247–262. Whiteaker, J.R., Suess, D.T., Prather, K.A., 2002. Effects of meteorological conditions on aerosol composition and mixing state in Bakersfield, CA. Environ. Sci. Technol. 36, 2345–2353. Widory, D., Roy, S., Le Moullec, Y., Goupil, G., Cocherie, A., Guerrot, C., 2004. The origin of atmospheric particles in Paris: a view through carbon and lead isotopes. Atmos. Environ. 38, 953–961. Wong, C., Li, X., Zhang, G., Qi, S., Peng, X., 2003. Atmospheric deposition of heavy metals in the Pearl River Delta, China. Atmos. Environ. 37, 767–776. Wuosmaa, A.M., Hager, L.P., 1990. Methyl chloride transferase: a carbocation route for biosynthesis of halometabolites. Science 249, 160–162.

a portable ATOFMS. Anal. Chem. 69, 4083–4091. Gard, E.E., Kleeman, M.J., Gross, D.S., Hughes, L.S., Allen, J.O., Morrical, B.D., Fergenson, D.P., Dienes, T., Gälli, M.E., Johnson, R.J., 1998. Direct observation of heterogeneous chemistry in the atmosphere. Science 279, 1184–1187. Gautam, M., Chitoor, K., Durbha, M., Summers, J.C., 1999. Effect of diesel soot contaminated oil on engine wear-investigation of novel oil formulations. Tribol. Int. 32, 687–699. Gillis, B.S., Arbieva, Z., Gavin, M.I., 2012. Analysis of lead toxicity in human cells. BMC Genom. 13, 344–356. Graedel, T., Keene, W., 1995. Tropospheric budget of reactive chlorine. Glob. Biogeochem. Cycl. 9, 47–77. Grandjean, P., Herz, K.T., 2015. Trace elements as paradigms of developmental neurotoxicants: lead, methyl mercury and arsenic. J. Trace Elem. Med. Biol. 31, 130–134. Guazzotti, S., Suess, D., Coffee, K., Quinn, P., Bates, T., Wisthaler, A., Hansel, A., Ball, W., Dickerson, R., Neusüß, C., 2003. Characterization of carbonaceous aerosols outflow from India and Arabia: biomass/biofuel burning and fossil fuel combustion. J. Geophys. Res.-Atmos. 108. https://doi.org/10.1029/2002JD003277. Gysel, M., Crosier, J., Topping, D., Whitehead, J., Bower, K., Cubison, M., Williams, P., Flynn, M., McFiggans, G., Coe, H., 2007. Closure study between chemical composition and hygroscopic growth of aerosol particles during TORCH2. Atmos. Chem. Phys. 7, 6131–6144. Hinz, K.P., Spengler, B., 2007. Instrumentation, data evaluation and quantification in online aerosol mass spectrometry. J. Mass Spectrom. 42, 843–860. Hjortenkrans, D.S., Bergbäck, B.G., Häggerud, A.V., 2007. Metal emissions from brake linings and tires: case studies of Stockholm, Sweden 1995/1998 and 2005. Environ. Sci. Technol. 41, 5224–5230. Huang, P.-C., Su, P.-H., Chen, H.-Y., Huang, H.-B., Tsai, J.-L., Huang, H.-I., Wang, S.-L., 2012. Childhood blood lead levels and intellectual development after ban of leaded gasoline in Taiwan: a 9-year prospective study. Environ. Int. 40, 88–96. Huang, R.J., Zhang, Y., Bozzetti, C., Ho, K.F., Cao, J.J., Han, Y., Daellenbach, K.R., Slowik, J.G., Platt, S.M., Canonaco, F., Zotter, P., Wolf, R., Pieber, S.M., Bruns, E.A., Crippa, M., Ciarelli, G., Piazzalunga, A., Schwikowski, M., Abbaszade, G., SchnelleKreis, J., Zimmermann, R., An, Z., Szidat, S., Baltensperger, U., El Haddad, I., Prevot, A.S., 2014. High secondary aerosol contribution to particulate pollution during haze events in China. Nature 514, 218–222. Keane, M.A., 2007. Catalytic conversion of waste plastics: focus on waste PVC. J. Chem. Technol. Biot. 82, 787–795. Keene, W.C., Pszenny, A.A., Jacob, D.J., Duce, R.A., Galloway, J.N., Schultz-Tokos, J.J., Sievering, H., Boatman, J.F., 1990. The geochemical cycling of reactive chlorine through the marine troposphere. Glob. Biogeochem. Cycl. 4, 407–430. Komárek, M., Ettler, V., Chrastný, V., Mihaljevic, M., 2008. Lead isotopes in environmental sciences: a review. Environ. Int. 34, 562–577. Laskin, A., Laskin, J., Nizkorodov, S.A., 2012. Mass spectrometric approaches for chemical characterisation of atmospheric aerosols: critical review of the most recent advances. Environ. Chem. 9, 163–189. Lee, C.S., Li, X.D., Zhang, G., Li, J., Ding, A.-J., Wang, T., 2007. Heavy metals and Pb isotopic composition of aerosols in urban and suburban areas of Hong Kong and Guangzhou, South China-evidence of the long-range transport of air contaminants. Atmos. Environ. 41, 432–447. Lee, S.H., Murphy, D.M., Thomson, D.S., Middlebrook, A.M., 2003. Nitrate and oxidized organic ions in single particle mass spectra during the 1999 Atlanta Supersite Project. J. Geophys. Res.-Atmos. 108. https://doi.org/10.1029/2001JD001455. Li, L., Huang, Z., Dong, J., Li, M., Gao, W., Nian, H., Fu, Z., Zhang, G., Bi, X., Cheng, P., 2011. Real time bipolar time-of-flight mass spectrometer for analyzing single aerosol particles. Int. J. Mass Spectr. 303, 118–124. Li, P., Lin, C., Cheng, H., Duan, X., Lei, K., 2015. Contamination and health risks of soil heavy metals around a lead/zinc smelter in southwestern China. Ecotoxicol. Environ. Saf. 113, 391–399. Li, Q., Cheng, H., Zhou, T., Lin, C., Guo, S., 2012a. The estimated atmospheric lead emissions in China, 1990–2009. Atmos. Environ. 60, 1–8. Li, Q., Cheng, H., Zhou, T., Lin, C., Guo, S., 2012b. The estimated atmospheric lead emissions in China, 1990–2009. Atmos. Environ. 60, 1–8. Liu, D.-Y., Rutherford, D., Kinsey, M., Prather, K.A., 1997. Real-time monitoring of pyrotechnically derived aerosol particles in the troposphere. Anal. Chem. 69, 1808–1814. Ma, L., Li, M., Zhang, H., Li, L., Huang, Z., Gao, W., Chen, D., Fu, Z., Nian, H., Zou, L., 2016a. Comparative analysis of chemical composition and sources of aerosol particles in urban Beijing during clear, hazy, and dusty days using single particle aerosol mass spectrometry. J. Clean. Prod. 112, 1319–1329. Ma, L., Li, M., Huang, Z., Li, L., Gao, W., Nian, H., Zou, L., Fu, Z., Gao, J., Chai, F., Zhou, Z., 2016b. Real time analysis of lead-containing atmospheric particles in Beijing during springtime by single particle aerosol mass spectrometry. Chemosphere 154, 454–462. McLennan, S.M., 2001. Relationships between the trace element composition of sedimentary rocks and upper continental crust. Geochem. Geophys. Geosyst. 2. https:// doi.org/10.1029/2000GC000109. Moffet, R.C., Desyaterik, Y., Hopkins, R.J., Tivanski, A.V., Gilles, M.K., Wang, Y., Shutthanandan, V., Molina, L.T., Abraham, R.G., Johnson, K.S., 2008a. Characterization of aerosols containing Zn, Pb, and Cl from an industrial region of Mexico City. Environ. Sci. Technol. 42, 7091–7097. Moffet, R.C., de. Foy, B., Molina, L.T., Molina, M.J., Prather, K.A., 2008b. Measurement of ambient aerosols in northern Mexico City by single particle mass spectrometry. Atmos. Chem. Phys. 8, 4499–4516. Murphy, D., Thomson, D., 1997. Chemical composition of single aerosol particles at Idaho Hill: positive ion measurements. J. Geophys. Res.-Atmos. 102, 6341–6352. Murphy, D., Hudson, P., Cziczo, D., Gallavardin, S., Froyd, K., Johnston, M., Middlebrook,

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Ecotoxicology and Environmental Safety 168 (2019) 53–63

J. Lu et al.

2014. Source and mixing state of iron-containing particles in Shanghai by individual particle analysis. Chemosphere 95, 9–16. Zhang, Y., Wang, X., Chen, H., Yang, X., Chen, J., Allen, J.O., 2009. Source apportionment of lead-containing aerosol particles in Shanghai using single particle mass spectrometry. Chemosphere 74, 501–507. Zhao, S., Chen, L., Yan, J., Chen, H., 2017. Characterization of lead-containing aerosol particles in Xiamen during and after Spring Festival by single-particle aerosol mass spectrometry. Sci. Total Environ. 580, 1257–1267. Zhao, Z.-Q., Zhang, W., Li, X.-D., Yang, Z., Zheng, H.-Y., Ding, H., Wang, Q.-L., Xiao, J., Fu, P.-Q., 2015. Atmospheric lead in urban Guiyang, Southwest China: Isotopic source signatures. Atmos. Environ. 115, 163–169. Zhou, J., Swietlicki, E., Berg, O.H., Aalto, P.P., Hämeri, K., Nilsson, E.D., Leck, C., 2001. Hygroscopic properties of aerosol particles over the central Arctic Ocean during summer. J. Geophys. Res.-Atmos. 106, 32111–32123. Zhu, L., Tang, J., Lee, B., Zhang, Y., Zhang, F., 2010. Lead concentrations and isotopes in aerosols from Xiamen, China. Mar. Pollut. Bull. 60, 1946–1955.

Xu, H., Han, S., Bi, X., Zhao, Z., Zhang, L., Yang, W., Zhang, M., Chen, J., Wu, J., Zhang, Y., Feng, Y., 2016. Atmospheric metallic and arsenic pollution at an offshore drilling platform in the Bo Sea: a health risk assessment for the workers. J. Hazard. Mater. 304, 93–102. Yao, H., Naruse, I., 2009. Behavior of lead compounds during municipal solid waste incineration. Proc. Combust. Inst. 32, 2685–2691. Yeung, M.C., Lee, B.P., Li, Y.J., Chan, C.K., 2014. Simultaneous HTDMA and HR-ToF-AMS measurements at the HKUST Supersite in Hong Kong in 2011. J. Geophys. Res-Atmos. 119, 9864–9883. Young, T.M., Heeraman, D.A., Sirin, G., Ashbaugh, L.L., 2002. Resuspension of soil as a source of airborne lead near industrial facilities and highways. Environ. Sci. Technol. 36, 2484–2490. Yu, X., Yuan, Z., Fung, Z., J.C.H., Xue, J., Li, Y., Zheng, J., Lau, A.K.H., 2014. Ozone changes in response to the heavy-duty diesel truck control in the Pearl River Delta. Atmos. Environ. 88, 269–274. Zhang, G., Bi, X., Lou, S., Li, L., Wang, H., Wang, X., Zhou, Z., Sheng, G., Fu, J., Chen, C.,

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