Tracing local sources and long-range transport of PM10 in central Taiwan by using chemical characteristics and Pb isotope ratios

Central Taiwan is among the most heavily polluted regions in Taiwan because of a complex mixing of local emissions from intense anthropogenic activities with natural dust. Long-range transport (LRT) of pollutants from outside Taiwan also contributes critically to the deterioration of air quality, especially during the northeast monsoon season. To identify the sources of particulate matter < 10 μm (PM10) in central Taiwan, this study performed several sampling campaigns, including three local events, one LRT event, and one dust storm event, during the northeast monsoon season of 2018/2019. The PM10 samples were analyzed for water-soluble ion and trace metal concentrations as well as Pb isotope ratios. Local sediments were also collected and analyzed to constrain chemical/isotopic signatures of natural sources. The Pb isotope data were interpreted together with the enrichment factors and elemental ratios of trace metals in PM10, and reanalysis data sets were used to delineate the sources of PM10 in central Taiwan. Our results suggested that Pb in PM10 was predominantly contributed by oil combustion and oil refineries during the local events (48–88%), whereas the lowest contributions were from coal combustion (< 21%). During periods of high wind speed, the contribution from natural sources increased significantly from 13 to 31%. Despite Pb represented only a small portion of PM10, a strong correlation (r = 0.89, p  < 0.001, multiple regression analysis) between PM10 mass and the concentrations of Pb, V, and Al was observed in the study area, suggesting that the sources of PM10 in central Taiwan can be possibly tracked by using chemical characteristics and Pb isotopes in PM10. Moreover, the Pb isotopic signals of PM10 collected during the LRT event confirmed the impact of LRT from Mainland China, and the chemical characteristics of the PM10 significantly differed from those of the PM10 collected during local events. This study demonstrates the robustness of using a combination of Pb isotopic compositions and chemical characteristics in PM10 for source tracing in complex and heavily polluted areas.

. Supplementary Fig. S1 illustrates variations in the daily average values of air quality parameters (including PM 10 , PM 2.5 , O 3 , and NO x /O 3 ratio provided by the Taiwan Environmental Protection Administration [TEPA]) covering this study's sampling periods (during the northeast monsoon in 2018 and 2019). All sampling campaigns were divided into local, LRT, and dust storm events based on the air mass back trajectory analysis, transport of nitric acid from outside Taiwan (reanalysis data), NO x /O 3 ratio, and Al concentration in PM 10 . The local events were subdivided into low- (11/25, 2018), moderate- (11/13-15, 2018), and high-wind-speed (12/7, 2018) events based on wind speed criteria (see Materials and Methods for the details). The PM 10 concentrations during all events in central Taiwan were high (Table 2), and most of them exceeded those stated in the Air Quality Guidelines provided by the World Health Organization (20 μg m −3 and 50 μg m −3 for annual mean and daily mean, respectively) 36 . In general, the PM 10 concentration was relatively low (15.7-74.0 μg/m 3 ) during the low-wind-speed event, while it reached the highest values during the high-wind-speed event (57.1-121 μg/m 3 ). A moderate correlation (r = 0.59, p = 0.01) between PM 10 and wind speed was found during the local events, suggesting that PM 10  2− ] = 16,445-23,725 ng/m 3 ) and heavy metals (V, Ni, As, Cd, and Pb) indicated worsening air quality caused by anthropogenic activities. By contrast, elevated PM 10 (78.1 μg/m 3 ) and Al concentration during the dust storm event (10/30-31, 2019) reflected greater contributions from crustal materials. To trace the source of PM 10 in central Taiwan, we further applied enrichment factors (EFs), elemental ratios, and the Pb isotope data in PM 10 ; this is discussed in the following sections. 10 . Elements, such as V and Ni, have been widely used as indicator elements of oil combustion 9,37 , and Mo is often regarded as a tracer for heavy oil combustion 38,39 . By investigating metal compositions of filterable stack total suspended particles emitted from industrial areas in Taiwan, Lin et al. 40 reported that Mn, Zn, and Pb are critical marker elements for electric arc furnace steel plants, and that As, Cd, Sb, and Pb are potential indicator elements for coal-fired power plants. The EFs of these elements, therefore, can be further used to discuss anthropogenic sources. The EFs in PM 10 at each study site were plotted against distance to a petrochemical complex to illustrate the distribution patterns of trace metals in this region. As depicted in Fig. 2, the EFs were high in the low-wind-speed local event, with the highest EFs of V (> 78), Ni (> 108), Cu (> 1056), and Mo (> 1478) at sites #4 and #5, the nearest sites to the petrochemical complex. Relative to the low-wind-speed event, the EFs decreased during the moderate-wind-speed event and reached the lowest values during the high-wind-speed local event. The EFs also varied significantly at sites, especially during the high-wind-speed local event, indicating that contributions from local sources changed at sites. During the LRT event, EFs of Fe and Ti had lower values than those observed during the local events, while high values were observed for most heavy metals. During the dust storm event, low EFs might have resulted from the dilution effect due to relatively higher contributions of crustal materials (Fig. 2).

Enrichment factors and elemental ratios in PM
To better assess the emission sources, elemental ratios such as Fe/Al, V/Ni, and Cd/Pb are often used as indicators of dust sources 41,42 , source of oil combustion [43][44][45] , and source of industrial activities 9,46 , respectively. The selected elemental ratios for PM 10 collected in this study are summarized in Table 2. High Fe/Al ratios (1.03-2.66) were found during the local events, while low Fe/Al ratios (0.58-0.90) were found during the LRT event. The higher Fe/Al during the local events indicated Fe emission from steel plant or oil combustion 40 A high correlation between V and Ni (r = 0.88, p < 0.001) was obtained for PM 10 collected during the local events, suggesting the presence of one major V-Ni source. V/Ni ratio showed a narrow range between 1.19 and 2.33 during the local events, and slightly higher V/Ni ratios (2.28-2.48) were observed during the LRT event. According to previous studies, higher V/Ni ratios were reported in heavy oil combustion (V/Ni = 3-4) 43 and ship emissions (V/Ni = 2.5-5) 44,45 , whereas lower V/Ni ratios might indicate additional Ni from other sources (especially oil combustion) 50 . Cd/Pb ratios varied between 0.014 and 0.038 during the local events. Chen et al. 24 found a similar Cd/Pb ratio (0.033) for local emissions in central Taiwan, and a lower Cd/Pb ratio (0.024) was observed during high PM loading episodes. Hsu et al. 51 also reported a Cd/Pb ratio of 0.030 for PM 10 during summer in Taipei, and Cd/Pb decreased to 0.024 and 0.018 during the northeast monsoon and Asian dust periods, respectively. The Cd/Pb ratios found during the local events were similar to those obtained from anthropogenic activities in Europe (0.022) 52 . By contrast, high Cd/Pb ratios (0.051-0.061) were found during the LRT event, and these values were not observed in Taiwan before, indicating PM originated from non-local pollutants. The high Cd/Pb ratios were reported for PM in megacities in China 53 , these high ratios possibly indicated the origins of PM from non-ferrous metal production 52 .
As mentioned above, Al, V, and Pb are marker elements for different sources; V/Al was plotted against Pb/ Al in PM 10 collected during the local events to illustrate sources contributed to these metals in central Taiwan. As shown in Fig. 3, at least three primary sources contributed to these metals in PM 10 during the local events. Besides, an additional source was identified in this region during the LRT event. Multiple regression analysis was performed between PM 10 and elemental Al, V, and Pb concentrations for PM 10 collected during the local events.  10 . We, therefore, further evaluate the potential of utilizing Pb isotope ratios of PM 10 for tracing sources of Pb in PM 10 in central Taiwan.
Pb isotope compositions of potential PM 10 sources in Taiwan. Anthropogenic sources. The major anthropogenic sources of Pb are emissions from oil combustion (including oil boilers, vehicle exhaust, and oil refineries), coal combustion, and high-temperature industrial processes (e.g., steel plants) 54 . Taiwan is an island with limited energy resources and mainly relies on imported resources from other countries (up to 98%). According to Taiwan's Bureau of Energy, oil, coal, and natural gas accounted for 48%, 29%, and 15%, respectively, of Taiwan's total primary energy consumption in 2018 55 . Since 2012, Taiwan has been importing crude oil from Saudi Arabia (31%), Kuwait (21%), and others in similar proportions. Taiwan has been imported coal mainly from Australia (35-50%) and Indonesia (26-40%) since 2012. The unique Pb isotopic signatures of these sources facilitate the distinguishing of Pb sources. Yao et al. 56 investigated the Pb isotope compositions of commercial   Fig. 4. Regarding Pb emissions in high-temperature industries, no Pb isotope data are available for Taiwan; therefore, constraining Pb isotope ratios for these emissions in the future is needed.
Natural source. Studies have demonstrated that, under high wind speeds, windblown dust influences the air quality in the downstream segment of the Choshui River, particularly during the northeast monsoon season 27,59,60 . However, these studies have not provided a quantitative estimation of the contribution of local dust to PM 10 in central Taiwan. Recently, Hsu et al. 25 attempted to estimate this contribution by using a receptorbased source apportionment model. Herein, we provide an alternative method for calculating the contribution based on the Pb isotope ratios of PM 10 and potential end-members. To constrain the isotopic signals of natural materials and further estimate their contribution to Pb in PM 10 , we analyzed sediments from the Choshui River catchment (Fig. 1) for their metal concentrations and Pb isotope ratios. Because sediments in downstream areas could be influenced by human activities, sampling was conducted in both the downstream (group A) and upstream (group B) segments of the Choshui River catchment (Fig. 1). The EFs of these sediments were calculated relative to the upper continental crust 61 , and the results are presented in Supplementary Fig. S2. Although the EFs of Cd were higher (EF Cd = 9.9 ± 8.6) downstream than upstream (EF Cd = 0.5 ± 0.2), most EF values were close to unity for sediments collected from the upstream and downstream segments of the Choshui River catchment. This indicates that the element contents of this river's sediments are similar to the average composition in the upper continental crust. All the sediments analyzed in this study exhibited higher Pb isotopic ratios (  Pb source of PM 10 in central Taiwan: local events. As shown in the triple Pb isotope plot (Fig. 4a), PM 10 during the low-wind-speed event (11/25, 2018) had the lowest Pb isotope ratios, with a 206 Pb/ 207 Pb ratio of 1.144-1.161 and a 208 Pb/ 207 Pb ratio of 2.419-2.434 (Table 3). These ratios were close to or within the range of those reported for gasoline and diesel in Taiwan, suggesting that oil combustion/refineries are the main sources of Pb during the low-wind-speed conditions. Under this low-wind-speed condition, PM 10 at sites #4 and #6 exhibited slightly elevated Pb isotope ratios, indicating the presence of Pb sources other than oil combustion (Fig. 4a). For instance, site #6, the southernmost site in the study region, exhibited high Pb isotope ratios ( 206 Pb/ 207 Pb = 1.161 and 208 Pb/ 207 Pb = 2.434) and a high ratio of Pb/Al (Figs. 3 and 4a). From a combination of geochemical constraints (i.e. higher Pb/Al and Pb isotope ratios), we inferred that the elevated Pb isotope ratios at sites #4 and #6 were the result of elevated contributions from coal-fired power plants and steel plants. Pb isotope emission signals from steel plants, however, are still required to further assess the contribution from such plants.
During the moderate- (11/13-15, 2018) and high-wind-speed (12/7, 2018) events, PM 10 had higher Pb isotope ratios compared with PM 10 observed during the low-wind-speed event, with a 206 Pb/ 207 Pb ratio of 1.157-1.168 and a 208 Pb/ 207 Pb ratio of 2.431-2.455 (Table 3, Fig. 4a). The higher Pb isotope ratios suggested that Pb originated from either sediments or coal combustion because of the overlap of ratios between Indonesian coal and local sediments. This overlap of isotopic signals may hamper the explanation of the source. However, these two potential sources can be differentiated using EF values. As illustrated in Figs. 2 and 4a, PM 10 at sites #4 and #5 during the high-wind-speed event had the highest Pb isotope ratios and the lowest EF of Pb (< 10), indicating that these high ratios were mainly contributed by sediments rather than by other sources. The high concentrations of Al (3107 and 3656 ng/m 3 , respectively) in PM 10 at these two sites also support the increased contribution of crustal materials during the high-wind-speed event, confirming that natural dust is the dominant source of PM 10 in central Taiwan during the northeast monsoon season.
In summary, PM 10 in central Taiwan was predominantly attributed to oil combustion processes (i.e., industrial activities from the petrochemical complex and vehicular emissions), whereas the signals from coal-fired power and steel plants varied between sites. When the wind speed increased, another crucial PM 10 Fig. S4). The European Centre for Medium-Range Weather Forecasts (ECMWF) Atmospheric Composition Reanalysis 4 (EAC4) reanalysis dataset reveals that a nitric acid plume formed in Southeast China and gradually moved northeastward to Taiwan (Supplementary Fig. S5). In this study, PM 10 samples were collected on October 4, 2019. As discussed previously, the high concentrations of ionic species (sulfate, nitrate, and ammonium) and heavy metals (V, Ni, As, Cd, and Pb) indicated that the air quality became increasingly polluted (Supplementary      (Table 3; Fig. 4b).
High Pb isotope ratios indicated that contaminants may have originated from China because such ratios in aerosol samples have commonly been observed there. An earlier study investigated the Pb isotope ratios in airborne particles in urban and suburban areas of Guangzhou 62 , revealing average Pb isotope ratios during winter of 1.1631 ± 0.0058 and 2.4579 ± 0.0081 for 206 Pb/ 207 Pb and 208 Pb/ 207 Pb, respectively (Fig. 4b). More recently, similar Pb isotope ratios ( 206 Pb/ 207 Pb = 1.1675 ± 0.0040 and 208 Pb/ 207 Pb = 2.4491 ± 0.0066) were observed in PM 2.5 in Guangzhou, suggesting that such ratios in PM have remained high in the PRD 63 . According to relevant studies, coal combustion became the major source of Pb in the atmosphere after the phasing-out of leaded gasoline, leading to more radiogenic isotope ratios being observed for particles in the atmosphere in China 64,65 . High Pb isotopic ratios were also reported for aerosols in areas with high levels of industrial emissions 46,66-69 (Fig. 4b).
Thus, the high Pb isotope ratios in our PM 10 samples collected during the LRT event along with low Fe/Al and high Cd/Pb ratios suggested that the pollutants were most likely transported from China to Taiwan; furthermore, these signals were not observed during the local events. During the LRT event, PM 10 collected at Cape Fugui (a regional background site for monitoring LRT from outside Taiwan located at the northern tip of Taiwan) also exhibited similar Pb isotope ratios ( 206 Pb/ 207 Pb = 1.163 and 208 Pb/ 207 Pb = 2.443, Fig. 4b).
During the dust storm event (10/30-31, 2019), the air mass back trajectory revealed that the air parcels primarily originated from Northern China and passed through Shanghai, a megacity and economic center in East China, before reaching Taiwan (Supplementary Fig. S4). The dust-mixing ratio estimated by the EAC4 reanalysis indicated that the dust storm was mainly derived from Northern China, with the dust plume gradually being transported to East China (Supplementary Fig. S6). When the dust storm passed through Shanghai, a nitric acid plume derived from East China gradually moved southward to the Taiwan Strait (Supplementary Fig. S7). During this dust event, PM 10 samples were collected for 2 days consecutively at site #5. The results indicated that PM 10 Fig. 4b). The EFs of most metals in the PM 10 collected during the dust storm event were low (< 343, Fig. 2), indicating that the PM 10 was a mixture of pollutants and natural dust. This was further supported by the elevated Al concentrations (2324 ng/m 3 ) in the collected samples. The Pb isotope ratios of PM 10 on the first day reflected that this dust storm collected pollutants in East China and then transported them to Taiwan, as depicted by the reanalysis dataset and the higher Pb isotope ratios found in PM from East China. On the second day of sampling during the dust event (defined as Transition), the Pb isotope ratios of PM 10 decreased toward those detected during the local events, suggesting that the contribution from local emissions (oil combustion/ refineries) became dominant. This again confirmed that oil combustion and oil refineries (characterized by low Pb isotopic compositions) are the major sources of Pb in PM 10 in central Taiwan.
Estimating the relative contribution to Pb in PM 10 . Because distinctive Pb isotope ratios were found for each end-member, we were able to estimate their relative contributions to Pb in PM 10 . We adopted a ternary mixing model to calculate the relative contributions to Pb in PM 10 using the following equations: where R PM10 is the observed 206 Pb/ 207 Pb (or 208 Pb/ 207 Pb) ratio of PM 10 , Ri is the assumed 206 Pb/ 207 Pb (or 208 Pb/ 207 Pb) ratio for each end-member, and fi is the fraction of the contribution of each end-member. The end-members discussed in this study (i.e., oil combustion/refineries, coal combustion, and sediments) were assigned accordingly, as shown in Fig. 4a. We assumed that the end-member oil combustion/refineries were the average isotopic signatures of the oil products (gasoline and diesel, 206 Pb/ 207 Pb = 1.146 and 208 Pb/ 207 Pb = 2.425) investigated in Taiwan and assumed that the end-member coal combustion was the average isotopic signature of Australian coal ( 206 Pb/ 207 Pb = 1.206 and 208 Pb/ 207 Pb = 2.487) since Australian coal occupied half of the coal imported into Taiwan. The Pb isotope ratios for the mixture of Australian coal and Indonesian coal (by import proportion) are also very close to those of Australian coal; therefore, we simplified the calculation by using Australian coal as the end-member. We also assumed that the end-member natural material was the average isotopic signature of sediments ( 206 Pb/ 207 Pb = 1.179 and 208 Pb/ 207 Pb = 2.479) collected in this study. A Bayesian mixing model, MixSIAR 70,71 , was employed to calculate each end-member contribution to Pb in PM 10 . This model incorporates the uncertainties of the isotopic signatures for each source, and it was successfully applied to assess Pb sources in isotopic mixtures quantitatively 72 . The model results revealed the contribution from oil combustion to be predominant (48-88%) during the local events, whereas coal combustion made a minor contribution (< 21%) in central Taiwan (Supplementary Table S2, Fig. 5). On the other hand, contributions from sediments increased significantly from 13 to 31% during the high-wind-speed event and were highly variable among sites. The high proportions of oil combustion suggested an approach for mitigating emissions in the future.
During the LRT and dust storm events, the Pb isotope ratios of PM 10 might have been overprinted by pollutants derived from China (as shown in Fig. 4b), and further complicated the contribution estimations. In such cases, Pb in PM 10 was assumed to be dominated by the LRT of pollutants, and the approach presented here should be able to delineate the PM 10 sources if the primary sources of Pb can be better constrained. (1)

Concluding remarks
This study investigated the chemical characteristics and sources of PM 10 during various events of the 2018/2019 northeast monsoon season in central Taiwan. High concentrations of ionic species were found during the lowwind-speed local event, suggesting that local pollutants accumulated when the atmospheric condition stagnated. By contrast, high concentrations of crustal elements (e.g., Al, Fe, and Ti) were found during the high-windspeed local event, suggesting the enhanced influence of local sediments. By employing EFs, elemental ratios, and Pb isotope ratios, we revealed an evident variation in the contributions from local sources. For instance, oil combustion was enriched in V and Ni and had the lowest Pb isotope ratios. Coal combustion was enriched in As, Sb, and Pb and had the highest Pb isotope ratios. Sediments were characterized by the unity of EFs and moderate Pb isotope ratios. This study also included a ternary mixing model of Pb isotopes for the source apportionment of Pb in PM 10 in central Taiwan. The contribution of Pb was dominated by oil combustion/refineries during local events (48-88%), whereas the contributions from coal combustion were lower (< 21%). The contributions from sediments were increased from 13 to 31% when the wind speed became high. All of the results were supported by the chemical characteristics of PM 10 and the reanalysis dataset. Furthermore, a strong correlation (r = 0.89, p < 0.001, multiple regression analysis) between PM 10 mass and the concentrations of Pb, V, and Al was observed in the study area, suggesting that the sources of PM 10 in central Taiwan can be possibly tracked by using these chemical characteristics of PM 10 . By combining Pb isotope ratios, elemental ratios, EFs, and the reanalysis dataset, this study improved the constraints of PM 10 sources during different events. Moreover, we demonstrated a multi-tracer approach to understand transport and the contributions of Pb in PM 10 from various sources, which serves as a powerful tool for delineating complex atmospheres impacted by complex emission sources.

Materials and methods
Sampling site and PM 10 collection. PM 10 sampling was conducted at six sites located in the rural-fringe areas of Changhua, Yunlin, and Chiayi Counties in central Taiwan (Fig. 1), where the air quality is reported to be among the worst in Taiwan 73 . Several obvious anthropogenic sources of PM exist, such as a coal-fired power plant (one of the largest in the world) in Taichung City, Changhua coastal industrial park in Changhua County, and a petrochemical complex (including a coal-fired power plant) in Yunlin County. Moreover, sediments in the Choshui River catchment are the major source of PM derived from natural materials. Details about the sampling sites, sampling period, wind speed, wind direction, temperature, precipitation, and relative humidity are summarized in Table 1. A total of five sampling campaigns were conducted during the northeast monsoon season to collect PM 10 Supplementary Fig. S5), and a low ratio of NO x /O 3 (see Supplementary Fig. S1). The low NO x /O 3 ratio reflected that the air mass could have been transported from long distances, as NO x has a shorter lifetime than O 3 in the atmosphere 74 , and NO x gets reacted faster than O 3 during long-range transport. In contrast to the LRT event, a local event did not have the conditions mentioned above. A dust storm event was defined as air masses originating from Northern China ( Supplementary Fig. S4), southeastward transportation of dust (Supplementary Fig. S6), and Al concentration > 1400 ng/m 3 in PM 10 75 . The local events were further divided into low-, moderate-, and high-wind-speed events based on the Beaufort wind scale 76 of < 3.3 m/s (calm, light air, and light breeze), 3.3-8 m/s (gentle breeze, moderate breeze), and > 8 m/s (fresh breeze, strong breeze), respectively. Note that the PM 10 samples were only collected at site #5 during the dust storm event because only one sampler was available.
PM 10 samples were collected following the TEPA PM 10 sampling protocol (NIEA A208). In brief, PM 10 samples were collected at a flow rate of 66 ± 3 m 3 h −1 on a polytetrafluoroethylene (PTFE) filter using a high-volume sampler (Tisch Environmental., Cleves, OH, USA) with a size-selective inlet (10 μm) attached on the rooftop (approximately 10 m above ground level). The sampling was conducted for 8-28 h, except for site #2 (2 h) on Nov 25, 2018. After collection, the filter was transferred into a plastic envelope and delivered to the conditioning room within a few hours. Furthermore, a total of 13 sediment samples were collected from eight sites (Fig. 1) to constrain the chemical and isotope signals of the natural source. The sediment samples were collected in both upstream and downstream segments of the Choshui River catchment with plastic bags, dried at 45 °C in an oven, ground and sieved through a 75 μm sieve, and stored in a desiccator.
Chemical analysis. The PTFE filter was weighted for particle mass concentration with a microbalance after equilibration at 25 ± 1.5 °C under a relative humidity of 40% ± 5% for 24 h. Next, 1/9 of the filter was cut using a ceramic cutter, and the aliquot was then digested with an acid mixture of 9 mL of concentrated HNO 3 , 3 mL of concentrated HCl, and 3 mL of concentrated HF using a microwave (CEM Corp., Matthews, NC, USA). A two-stage heating procedure was employed; first, the mixture was heated to 170 °C over 20 min and maintained at this temperature for 10 min, followed by another round of heating to 200 °C over 7 min and maintaining for  Supplementary Tables S5 and S6, respectively. For the ion concentration, a sample aliquot of the filter was extracted with 50 mL of Milli-Q water in an ultrasonic bath for 30 min, followed by settling for 30 min. The solution was then filtered through a 0.45 μm PVDF filter (Merck KGaA, Darmstadt, Germany). Ion concentrations (SO 4 2− , NO 3 − , NH 4 + , and Cl − ) were measured using ion chromatography (Thermo-Fisher Scientific, Waltham, MA, USA) with analytical precision better than 10% (RSD).
Pb isotope analysis. An aliquot of the digested sample was transferred into an acid-cleaned PFA beaker.
This solution was evaporated and re-dissolved with 2 mL of 2 M HNO 3 and 0.07 M HF. The Pb fraction was extracted using Sr-spec ion exchange resin (Eichrom Technologies Inc., Lisle, IL, USA) following the steps modified from Pin et al. 77 . An international reference material (NIST 1648a) was also processed for each purification batch to assess the column chemistry performance. Pb was purified under a Class-10 laminar flow bench in a Class-10,000 clean room. The total procedural blanks for Pb were < 80 pg. Pb isotope ratios were measured using HR-MC-ICP-MS (Neptune PLUS, Thermo-Fisher Scientific) at the Institute of Earth Sciences, Academia Sinica (AS-IES). Standards and samples were doped with thallium (Tl) (NIST 997; 203 Tl/ 205 Tl ratio of 0.418673) to correct for instrumental mass fractionation 78 . Two standard reference materials (NIST SRM 981 and NIST SRM 1648a) were analyzed to assess the accuracy and long-term precision of the analytical protocol developed at AS-IES. The measured Pb isotope ratios for these international reference materials were in good agreement with the recommended values and are listed in Supplementary Table S7. The analytical uncertainties (2SD) for 206 Pb/ 207 Pb and 208 Pb/ 207 Pb were ± 0.0002 (n = 69) and ± 0.0003 (n = 69), respectively. Pb isotope ratios were reported as 206 Pb/ 207 Pb and 208 Pb/ 207 Pb in this study. Enrichment factor. The EF has been widely used to examine the contributions from natural and anthropogenic sources in aerosols [79][80][81] . The EF of elements was calculated using Eq. (3): where (Xi/Al) PM is the concentration ratio of element Xi to Al in PM, and (Xi/Al) Crust is the concentration ratio of element Xi to Al in the upper continental crust 61 . In general, EF values close to unity indicate the predominance of crustal sources; EF values ≥ 5 indicate a significant contribution from noncrustal sources; and EF values higher than 10 indicate essentially anthropogenic origins 24,80,82 . Reanalysis datasets. The EAC4 global reanalysis dataset provided by the Copernicus Atmosphere Monitoring Service (CAMS) was applied to provide additional constraints on the sources and transportation of pollutants in this study. EAC4 reanalysis combines model data with global observations into a globally complete and consistent dataset; the dataset used in this study was generated using CAMS information (2020) 83 . The spatial resolution of the dataset was 0.75° latitude by 0.75° longitude, with a temporal resolution of 3 h.
In addition, air mass back trajectory analysis was used to track the origins of the air parcels transported to the study sites. Back trajectories were calculated using the HYSPLIT model maintained by the US National Oceanographic and Atmospheric Administration with a spatial resolution of 1° latitude by 1° longitude in the meteorological dataset 84  www.nature.com/scientificreports/ Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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