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Source−Receptor Relationship Analysis of the Atmospheric Deposition of PAHs Subject to Long-Range Transport in Northeast Asia Yayoi Inomata,*,†,‡,§ Mizuo Kajino,§,∥,⊥ Keiichi Sato,‡ Junichi Kurokawa,‡ Ning Tang,† Toshimasa Ohara,# Kazuichi Hayakawa,† and Hiromasa Ueda¶ †

Kanazawa University, Kakuma-machi, Kanazawa, Ishikawa, 920-1154, Japan Asia Center for Air Pollution Research, 1182, Sowa, Nishi-ku, Niigata, Niigata, 950-2144, Japan § Meteorological Research Institute, 1-1, Nagamine, Tsukuba, Ibaraki, 305-0052, Japan ∥ Faculty of Life and Environmental Sciences, University of Tsukuba, 1-1-1 Ten-noudai, Tsukuba, Ibaraki, 305-8572, Japan ⊥ RIKEN Advanced Institute for Computational Science, 7-1-26 minatojima-minamimachi, Chuo-ku, Kobe, Hyogo, 650-0047, Japan # National Institute for Environmental Studies, 10-2 Fukasaku, Miharu, Tamura, Fukushima, 963-7700, Japan ¶ Disaster Prevention Research Institute, Kyoto University, Gokasho, Uji, Kyoto, 611-0011, Japan ‡

S Supporting Information *

ABSTRACT: The source−receptor relationship analysis of PAH deposition in Northeast Asia was investigated using an Eulerian regional-scale aerosol chemical transport model. Dry deposition (DD) of PAH was controlled by wind flow patterns, whereas wet deposition (WD) depended on precipitation in addition to wind flow patterns. The contribution of WD was approximately 50−90% of the total deposition, except during winter in Northern China (NCHN) and Eastern Russia (ERUS) because of the low amount of precipitation. The amount of PAH deposition showed clear seasonal variation and was high in winter and low in summer in downwind (South Korea, Japan) and oceanic-receptor regions. In the downwind region, the contributions from NCHN (WD 28−52%; DD 54−55%) and Central China (CCHN) (WD 43−65%; DD 33−38%) were large in winter, whereas self-contributions (WD 20−51%; DD 79−81%) were relatively high in summer. In the oceanic-receptor region, the deposition amount decreased with distance from the Asian continent. The amount of DD was strongly influenced by emissions from neighboring domains. The contributions of WD from NCHN (16−20%) and CCHN (28−35%) were large. The large contributions from China in summer to the downwind region were linked to vertical transport of PAHs over the Asian continent associated with convection.

1. INTRODUCTION The primary emission sources of polycyclic aromatic hydrocarbons (PAHs) to the atmosphere include the incomplete combustion of domestic coal, oil, gas, and domestic biomass (e.g., wood and straw), vehicle emissions (e.g., diesel engines, aircrafts, shipping, railways, automobiles, off-road vehicles, and machinery), open biomass burning, oil refining processes, waste incineration, and industrial activities.1 PAHs are recognized as carcinogenic, toxic, and mutagenic compounds by the International Agency for Research on Cancer (IARC).2,3 In particular, benzo[a]pyrene (BaP) is now classified as a group 1 human carcinogen (http://monographs.iarc.fr/ENG/Classification/). Northeast Asia is the most polluted area in the world in regard to PAHs, due to large anthropogenic emissions.4 In particular, PAH emissions from China constitute more than 90% of the emissions from Northeast Asia, according to the Regional Emissions Inventory in Asia (REAS-POP).5 It has been reported that particulate-phase PAH concentrations in © XXXX American Chemical Society

Chinese cities were 3−180 times greater than those in Japanese and Korean cities.6−12 Lang et al.13 estimated that PAHs emitted from China influenced neighboring countries (such as Russia, Mongolia, and Japan) within 2−4 days after emission. The transport patterns of PAHs vary greatly and depend on PAH emission density, meteorological conditions (such as westerlies), climatological conditions (such as the East Asian Monsoon), and local topographical forcing.14 It has also been reported that approximately 80% of 16 specific PAHs transported across the eastern boundary of China were concentrated near 30° N.15 During long-range transport, particulate PAHs undergo both homogeneous and heterogeneous oxidation. PAHs are removed Received: February 19, 2017 Revised: June 22, 2017 Accepted: June 23, 2017

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DOI: 10.1021/acs.est.7b00776 Environ. Sci. Technol. XXXX, XXX, XXX−XXX

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Environmental Science & Technology

variables, to the RAQM2-POP. The Final Operational Global Analysis Data from the National Centers for Environmental Prediction (ds083.2: http://rda.ucar.edu/datasets/ds083.2) provided initial and boundary conditions for the WRFV3 (http://rda.ucar.edu). The Mellor−Yamada−Janjić model was used to calculate the planetary boundary layer.26 The six-class scheme WSM6 was used for the cloud microphysics parametrization. The subgrid-scale cumulus parametrization,27 the land surface model28 (Noah LSM), longwave radiation,29 and shortwave radiation30 were considered. In the RAQM2, physical and chemical submodules were implemented, such as advection,31 gas-phase chemistry,32 secondary organic aerosol formation mechanisms,33 aqueous phase chemistry in cloud and rainwater droplets as well as aerosol water,34,35 new particle formation,36 aerosol dynamics (condensation, evaporation, Brownian coagulation),23 dry deposition,37−40 Cloud Condensation Nuclei activation,41 Ice Nuclei activation,42 cloud microphysics,43 collision of aerosols with grid scale rain, snow and graupel,23 and wet scavenging due to subgrid-scale convection (Asymmetrical Convective model).44 Details are described in Kajino et al.45 for the gas−particulate partitioning and oxidation was considered based on the Multicompartment POP transport model (MSCE-POP).24 Dominant processes included in RAQM2-POP are listed in Supporting Information Table S1. PAH partitioning between the gas and particulate phases was performed by the Junge−Pankow model using the subcooled liquid vapor pressure (Table S2).46,47 The oxidation of PAH was considered for gas and particulate phases reacting with OH and O3 radicals, which are temperature-dependent degradation rate constants (Table S3). The dry deposition for gases used were the parametrization scheme of Zhang et al.48 and Wesely’s parametrization.49 For the dry depositions of aerosols and cloud droplets, the parametrization of Zhang et al.50 was used for aerodynamic and surface resistances. The dry deposition velocity was calculated by the scheme developed by Venkatram and Pleim.51 The gravitational setting was developed by Binkowski and Shankar.52 The details of the dry deposition were described in Kajino et al.23 For wet deposition, CCN activation and subsequent cloud microphysical processes were parametrized based on Abdul-Razzak and Chan40 and single moment cloud microphysics parametrization.42 Wet scavenging was considered using the Asymmetrical Convective Model.43 The below-cloud scavenging process was considered to be intermodal coagulation with falling hydrometers, such as rain, snow, and graupel.23 The details of these schemes for the PAH simulations are provided in Inomata et al.22 The model domains cover most of the Northeast Asian countries. The horizontal grid resolution was 60 km on a Lambert conformal map projection. There were 27 vertical layers in the WRFV3 from the ground surface to 100 hPa. These layers were interpolated to 13 layers from the ground to 10 km, after preserving continuity in the mass continuity model.53 Simulations were run with a spin-up period of 3 days. The west−northwest boundary condition of the PAH transport was set to zero because China is located in the western part of the calculated domain and is the predominant PAH-emitting region in Northeast Asia.4,5 We also assumed a value of zero for transport from south−southeast Asia because no emission data were available. Concentrations, dry deposition, and wet deposition of PAH were outputted on an hourly basis.

from the atmosphere by dry and wet deposition. It has been reported that approximately 30−40% of PAHs in sediment in the coastal regions of South China were derived from atmospheric deposition.16 Because of their persistent characteristics, PAHs tend to accumulate in sediments and re-enter the water column. Furthermore, PAHs deposited in aquatic environments can be converted to monohydroxyl (OH)PAHs, which act on calcified tissues and suppress osteoblastic and osteoclastic activity.17,18 The bioaccumulation of these PAHs and their derivatives in the aquatic environment strongly affect the ecosystem via food chains. Considering that the deposition of PAHs is related to marine toxicity in the downwind region, it is necessary to quantitatively evaluate the wet and dry deposition of PAHs in Northeast Asia. Several studies have investigated wet and dry deposition of PAHs.16 However, these results were based on observational data, resulting in a limited ability to elucidate the spatial and temporal distribution of deposition in Northeast Asia. Model simulation can be very useful to better understand the spatial and temporal distributions of PAH concentrations and deposition. By using model simulations, inter-regional source− receptor relationship (SRR) analyses have been widely conducted to investigate the transboundary transport of several species of air pollutants, including O3 concentrations,19 SO42− deposition,20 and NO3− deposition.21 The SRR is an effective analytical method for evaluating the contributions from various source regions to receptor regions. Furthermore, the SRR facilitates the assessment of the impacts of sectorial emissions reductions to help plan environmental policies. So far, only one study has used SRR to analyze PAH concentrations by using the Regional Air Quality Model 2 for Persistent Organic Pollutants (RAQM2-POP).5,22,23 It is necessary to investigate the PAH deposition by SRRs largely because of the toxicity of PAHs. Therefore, in this study, we investigated the relative contribution of PAH deposition from sources to receptor regions associated with long-range transboundary transport in Northeast Asia. Chrysene (Chr, 4-rings), BaP (5-rings), and indenopyrene (IcdP, 6-rings) were selected to be representative of PAHs in this study. The estimation of dry and wet deposition of PAH using the SRR is a novel approach. Model performance was evaluated through comparisons with observations of PAH deposition.

2. MATERIALS AND METHODS 2.1. Model Description. An offline coupled chemical transport model, the Regional Air Quality Model 2 − Persistent Organic Pollutants version (RAQM2-POP), was used to simulate the deposition of PAHs. The model was developed based on the European Monitoring Evaluate Program (EMEPPOP model), which was designed for assessment of transport and accumulation of persistent organic pollutants (POPs) in the framework of the development of air quality policies in Europe under the Convention on Long-range Transboundary Air Pollution.24 We have previously investigated the distribution of particulate PAH concentrations in Northeast Asia5 and the SRR of particulate PAH concentrations22 using this model. In this study, we used the same version that we used to analyze the SRRs of the PAH concentrations.22 Because the details of the model have been previously reported,22 we include only a brief description of the PAH simulation here. The Weather Research and Forecasting model version 3.325 (WRFV3) was used to provide meteorological fields, such as wind, temperature, water mixing ratio, precipitation, and surface B


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reductions should be sufficiently small that nonlinear effects due to photochemical reactions with oxidants such as NOx are less significant. Several studies have adopted reduction rates of 10−25% over East Asia.57−59 In this study, the reduction rate was set to 20%. The domain was divided into six source−receptor regions: northern China (north of 40° N, NCHN), central China (30° N−40° N, CCHN), southern China (south of 30° N, SCHN), eastern Russia (ERUS), South Korea (SKOR), and Japan (JPN). This division was performed to better reflect the SRR across different regions and was based on the classification of Kajino et al.20 Three oceanic regions (the Yellow Sea and East China Sea, YEC; the Sea of Japan, SOJ; and the Northwest Pacific Ocean, NWP) were set as oceanic-receptor regions (Figure S1) because some PAHs are a bioaccumulation concern and cause acute and chronic toxicity to marine life.17,60 The SRR for PAH depositions was calculated as

The model performance was evaluated by comparing the observed and simulated data. During the available emissions inventory period (2000−2005), observational data were sparse at Niigata (138.85° E, 37.81° N; coastal site for the Sea of Japan) from August to December 2005. We also used the observed PAH concentrations in the precipitation from November 2013 to December 2014 at the Noto site (136.9° E, 37.5° N, 2.1 km downwind of the coastline) to investigate the model performance. The emissions inventory of 2005 was used to simulate PAH after 2006. Different years’ data of the emissions inventory were used for the simulation, although the meteorological data were used for the corresponding time period. 2.2. Emission Inventory. The PAH emissions data were available from REAS-POP ver1.0.5 The area covered in REASPOP ver1.0 includes China, the eastern part of Russia, Mongolia, North Korea, South Korea, Japan, and Taiwan. The PAH emissions data were gridded at 0.5° × 0.5° and interpolated to model grids with 60 km × 60 km resolution. The PAH emission period was from 2000 to 2005. The temporal resolution was one month. Because the details of REAS-POP ver1.0 have been previously described,5 we provide only a brief description here. PAH emissions were estimated as the product of the fuel consumption rate and the emission factor. Fuel consumption rates were divided into three categories: stationary, on-road mobile, and open biomass burning sources. The fuel consumption rates of the stationary sources were categorized by fuel types, i.e., hard coal, brown coal, and derived coal (coke oven), natural gas, motor gasoline, kerosene, diesel oil, heavy fuel oil, crude oil, fuel wood, crop residue, animal waste, municipal waste, and charcoal. The traffic fuel consumption rates of the on-road mobile sources were classified into seven types (light-duty gasoline vehicles, heavy duty gasoline vehicles, gasoline buses, diesel buses, gasoline cars, diesel cars, and motorcycles). The fuel consumption data for stationary and onroad mobile sources were derived from the REAS,54 and those for open biomass burning were derived from the Global Fire Emissions Database version 3 (GFEDv3).55 REAS-POP ver1.0 included emissions data for the following 16 PAHs: two aromatic rings: naphthalene (NaP); 3 rings: acenaphthylene (Acy), acenaphthene (Ace), fluorene (Fle), phenanthrene (Phe) and anthracene (Ant); 4 rings: fluoranthene (Flu), pyrene (Pyr), benz[a]anthracene (BaA) and chrysene (Chr); 5 rings: benzo[b]fluoranthene (BbF), benzo[k]fluoranthene (BkF), benzo[a]pyrene (BaP) and dibenz[a,h]anthracene (DahA); and 6 rings: indeno[1,2,3-cd]pyrene (IcdP) and benzo[g,h,i]perylene (BghiP). These PAHs are listed as priority pollutants by the U.S. Environmental Protection Agency.56 It is worth noting that re-emission of PAHs from the ocean is not included in this model. 2.3. Source−Receptor Relationship Analysis Methods. The SRR is a very useful tool to estimate the contribution of PAHs emitted from certain regions. In our previous research, we investigated the SRR analysis of particulate PAH concentrations in 2005.22 By using the same model version, we investigated the SRR of PAH deposition. Therefore, only a short description of the SRR method is presented here. To analyze the SRR, we used a brute force method, in which we conducted two different runs: a control run and a reducedemissions run. The control run was based on the original PAH emissions, whereas the reduced-emissions run was based on reduced PAH emissions from each region. The emissions

R i , j(%) =

Dj − Di − 20%, j Dj

× 5 × 100 (1)

where Ri,j is the contribution of the ith emission source to the jth receptor; Dj is the amount of deposition at receptor j under the full emissions scenario; and Di‑20%,j is the deposition at the jth receptor under a 20% emissions reduction from the ith emission source. The 5 is a correction factor because the reduction rate against the full emissions is 20%. 2.4. Observation of PAH in Precipitation and Chemical Analysis. Because the main focus of this study is SRR analysis by model simulation, the details of the observation and chemical analysis method are briefly described. Observational data were collected at Noto (136.9° E, 37.5° N, 2.1 km downwind of the coastline), a remote monitoring site facing the Sea of Japan. Sampling at Noto was conducted at a height of 3 m above the ground.12 The sampling interval was one week from November 2013 to October 2014. Precipitation samples were collected in stainless steel vials (30 L) after filtering the aerosol samples with a Millipore filter (pore size 0.45 μm) using a bulk sampler (inlet diameter 30 cm). We positioned two samplers to collect a large volume of precipitation samples. Particulate PAHs were collected in a glass filter (GC-50, Advantec Co. Ltd.) and extracted in benzene−ethanol solution by ultrasonic methods. Once the particulate PAHs were removed, the soluble phase PAHs were collected in a C18 disk filter (3M) by filtration. The PAHs collected on the C18 disk filter were also extracted by benzene−ethanol solution. The internal standards (deuterated PAHs such as NaP-d8, Aced10, Phe-d10, Pyr-d10, BaP-d12) were added to the precipitation samples prior to the extraction. The PAHs in benzene−ethanol solutions were washed three times, first with sodium hydroxide solution (5%), then with sulfuric acid solution (20%), and finally with distilled water. After DMSO was added to the extracted benzene solution, the solution was dried with a rotary evaporator. The residue was then dissolved in 900 μL of ethanol, and the resulting solution was analyzed by highperformance liquid chromatography (HPLC) with fluorescence detection12 after it had passed through a membrane filter (HLC-DISK3, Kanto Chemical CO., Inc.). The EPA610 PAH Mix (SUPELCO Co. Ltd.) was used as the standard. Fourteen PAHs (NaP, Ace, Fle, Phe, Ant, Flu, Pyr, BaA, Chr, BaP, BbF, BkF, BghiP, and IcdP) were detected. C


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Figure 1. Horizontal distributions of the dry (DD) and wet (WD) deposition of BaP in winter (DJF) and summer (JAS): (a) wet deposition in winter, (b) dry deposition in winter, (c) wet deposition in summer, and (d) dry deposition in summer. The units are mg m−2 3 months−1. The horizontal black lines indicate the boundaries of the 3 Chinese domains.

3. RESULTS AND DISCUSSION 3.1. Model Validation Using the Observational Data. The RAQM2-POP model performance for wet deposition was evaluated by comparing the observed and simulated precipitation data from November 2013 to October 2014. We also used the observed data from Niigata, a coastal site on the Sea of Japan, from August 2005 to May 200661 because the 2005 data were covered in the available fuel consumption data for the PAH emissions inventory. We evaluated the model performance using total wet deposition (sum of the water-soluble and -insoluble phases). In this study, we focused on Chr (4-rings), BaP (5-rings), and IcdP (6-rings) as the representatives for their respective ring-number classes. It is worth noting that BaP and IcdP mostly existed in the particulate phase in the atmosphere, whereas Chr existed in both the gaseous and particulate phases. The model performance was evaluated by comparing observed and simulated precipitation amounts and concentrations of each species in the precipitation (Figure S2). The results of the statistical analysis are summarized in Table S4. More than 68% of the modeled data are within factor of 5 of the observed data, which indicates that the modeling results agree with the observed data within one-fifth to five times. Although several values are not within a factor of 10, these comparisons suggest that the modeled data are in good

agreement with a 5-fold factor. We also compared the observational data at Mt. Taishan,62 China with the simulated data. In this case, average values during the observation periods (September 2005 to August 2007), which have been previously reported in the literature,63 were used for the comparison. The observed average values (Chr 3.11 ng L−1(range 0.51−20.83 ng L−1); BaP 2.26 ng L−1(range 0.47−31.26 ng L−1); For IcdP, no data) and simulated average values (Chr 0.9 ng L−1 (range ∼1 × 103 ng L−1); BaP 4.53 ng L−1 (range ∼3 × 103 ng L−1)) are on the same order. These results indicate that the model simulated reasonably well the wet deposition of PAHs in the source and receptor regions. Although the model simulation was conducted using the 2005 emissions data, we consider the model to have simulated the observed wet deposition of PAHs reasonably well. 3.2. Dry Deposition and Wet Deposition of PAH in Northeast Asia. The dry deposition and wet deposition of PAH in winter (December, January, and February; DJF) were both larger than they were in summer (July, August, and September; JAS) (BaP, Figure 1; Chr and IcdP, Figure S3). The greatest amounts of dry deposition occurred in the North China Plain (e.g., the Hebei province), the Northwestern zone (e.g., the Shanxi and Shaanxi provinces), and the Southwestern zone (e.g., the Sichuan, Guizhou, and Guangxi provinces). The large dry deposition region is consistent with the large D


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Figure 2. Estimation of the total (wet + dry) deposition (TD) of BaP (left) and the relative contributions (right) to each domain: (a) NCHN, (b) CCHN, (c) SCHN, (d) ERUS, (e) SKOR, (f) JPN, (g) YEC, (h) SOJ, (i) NWP.

emissions and high concentrations in the region.5,22 The largest amounts of wet deposition occurred in the Sichuan and Guizhou provinces in China. Large amounts of wet deposition also occurred in the YEC region and the western part of the SOJ region. It is worth pointing out that the wet deposition in the northern region of the Asian continent was small in winter. The seasonal distributions of wet deposition of PAHs were quite similar to the horizontal distribution of precipitation, as shown in Figure S4. Wet deposition of PAH depended on the surface concentrations as well as the concentrations in the entire column up to the cloud top and the water drop mixing ratios in the atmosphere. Large amounts of wet deposition of PAH occurred in the high concentration regions as well as in the regions with greater precipitation. 3.3. Emissions, Dry Deposition, and Wet Deposition of PAHs. The annual emissions and accumulated dry and wet deposition of PAHs are listed in Table S5. In the three Chinese domains (NCHN, CCHN, and SCHN), emissions of PAH were 3−11 times larger than the total (sum of dry and wet) deposition. The emissions in ERUS was also 4 times larger than the total deposition. In these domains, the amounts of wet deposition were larger than those of dry deposition. However, the emissions from SKOR and JPN were less than their deposition amounts. These results suggest that China and ERUS are significant PAH source regions that influence the

environment in downwind regions of Northeast Asia. In the oceanic receptor domains, the largest deposition occurred in the YEC, followed by the SOJ and the NWP, indicating that the deposition decreases with distance from the Asian continent. 3.4. Estimates of PAH Deposition in the Source− Receptor and Oceanic Receptor Domains. Figure 2 shows the monthly variation of the total BaP deposition and the relative contributions in the source−receptor domains. The wet deposition pattern for each domain was divided into two cases. As shown in NCHN (Figure 2a) and the ERUS (Figure 2d), the largest deposition occurred in spring (April), and the amount of deposition was also large in autumn. Small amounts of precipitation during the period from December to March resulted in smaller amounts of BaP deposition. During this period, the relative contributions of dry deposition were large and accounted for 80% of total deposition in NCHN. In other domains (Figure 2b, c, e, f), total deposition was large in winter and small in summer. The relative contribution of wet deposition accounted for more than 80% of the total deposition. Contributions from its own domain were large in CCHN (36−78%) and SCHN (51−89%). In SKOR and JPN, the relative contributions of WD from CCHN (SKOR 41− 59%; JPN 29−52%) and NCHN (SKOR 12−33%; JPN 42− 60%) were large in winter and decreased toward the summer. The relative contributions from its own domain (SKOR 10− E


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Figure 3. Spatial distributions of the relative contributions (%) of the dry deposition of BaP in the emission source regions in winter: (a) NCHN, (b) CCHN, (c) SCHN, (d) ERUS, (e) SKOR, (f) JPN, and summer (g) NCHN, (h) CCHN, (i) SCHN, (j) ERUS, (k) SKOR, (l) JPN.

summer, the relative contributions from SCHN-WD (6− 18%), ERUS-WD (10−25%), SKOR-WD (4−9%), and JPNWD (6−13%) increased. The relative contributions from NCHN-WD (43−48%) and CCHN-WD (41−45%) were also large in the NWP in winter, whereas the relative contributions from JPN-WD (10−24%) and ERUS-WD (6− 25%) increased in summer. The tendencies of monthly variation of Chr and IcdP are also shown in Figures S5 and S6, respectively. The seasonal variations of WD as well as DD are similar to those of BaP. However, the relative contributions of DD to TD for Chr in CCHN and NCHN are relatively larger than those of other species. It is noted that the relative contribution of IcdP is similar to that of BaP. Chr exists in both the gas and particulate phases depending on the temperature, whereas BaP and IcdP predominantly exist in the particulate phase. The phase (gas or particulate) might be reflected by these differences. 3.5. Spatial and Temporal Distributions of PAH Deposition Using the SRR. In this section, we discuss the relative contributions from the source regions using the SRR for the dry and wet deposition separately. 3.5.1. Spatial Distributions and Areal Average of Dry Depositions. Figure 3 shows the spatial distributions of the seasonally averaged contributions of the six source−receptor domains to the dry deposition of BaP (Chr, Figure S7; IcdP, Figure S8). The seasonally averaged relative contributions from the six source−receptor domains to the nine receptor domains of the three PAHs are listed in Table S6. It is noted that the spatial distribution of the SRR is a heterogeneous distribution,

17%; JPN 15−57%) were increased in summer for SKOR and JPN. These characteristics suggest that the transport of BaP from the Asian continent is controlled by the westerlies and by the East Asian Monsoon (location of the Pacific High). Lang et al.13 investigated the interannual variation of BaP outflow from China, where the mean transport occurred in the boundary layer and moved offshore from mainland China. They reported that the strongest outflow of BaP occurred in the winter from November to February in 2005, which was also the year analyzed in this study. The SRR results in winter would represent a stronger outflow of PAHs. Figure 2g−i also shows monthly total deposition of BaP and the relative contribution from the six source−receptor domains to the three oceanic−receptor domains (YEC, SOJ, and NWP) in 2005. The total deposition of BaP was largest in the YEC, followed by the SOJ and the NWP, indicating that total deposition amounts decrease with distance from the Asian continent. The total deposition amount was characterized by clear seasonal variations with highs in the winter and lows in the summer. The relative contributions of monthly wet deposition versus the monthly total deposition were 83−97% in the YEC (Figure 2g), 89−96% in the SOJ (Figure 2h), and 90−97% in the NWP (Figure 2i). In the YEC, the largest contribution in winter was CCHN-wet deposition (WD) (61− 75%), and the second largest contribution was NCHN-WD (15−25%). In summer, the relative contribution from SCHNWD (15−40%) increased. In the SOJ, the largest contribution in the winter was NCHN-WD (41−73%), and the second largest contribution was CCHN-WD (14−50%). In the F


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Figure 4. Spatial distributions of the relative contributions (%) of the wet deposition of BaP in the emission source regions in winter: (a) NCHN, (b) CCHN, (c) SCHN, (d) ERUS, (e) SKOR, (f) JPN, and summer (g) NCHN, (h) CCHN, (i) SCHN, (j) ERUS, (k) SKOR, (l) JPN.

These tendencies were consistent with the wind flow pattern, as shown in Figure S4. 3.5.2. Spatial Distributions and Areal Average of Wet Deposition. The effect of transboundary transport of BaP was also clearly seen in wet deposition (Figure 4). The relative contribution from each source to receptor domain of Chr and IcdP are also shown in Figures S9 and S10. The average values of the relative contribution for the three PAHs are listed in Table S7. In winter, emissions from NCHN, CCHN, and ERUS greatly influenced the downwind regions. The relative contribution from NCHN was large in SOJ (60%), JPN (52%), and NWP (46%) (Figure 4a). The relative contribution from CCHN was large for the YEC (73%), SKOR (65%), JPN (43%), SOJ (33%), and NWP (47%) (Figure 4b). The contribution from ERUS was large in the northern part of the SOJ, although the relative contribution was small (4%) (Figure 4d). In summer, relative self-contributions (contribution from its own domain) were large in the three Chinese domains (NCHN 55%; CCHN 87%; SCHN 83%) and in ERUS (44%). In the downwind regions (SKOR and JPN), transport from CCHN (SKOR 62%; JPN 24%) was large, as was the self-domain (SKOR 20%; JPN 51%). In the YEC, the largest contribution was from CCHN (78%), and second largest contribution was from SCHN (16%). In the SOJ, transports from NCHN (20%), CCHN (35%), and ERUS (21%) were large. Transports derived from NCHN (16%), CCHN (28%), SCHN (10%), and ERUS (19%) were also large in the NWP. The contribution of JPN (21%), which is located upwind, also increased in the NWP.

and the resulting values at the source−receptor domains are often more than two times higher than the regional average.20,23 Dry deposition of BaP in the three Chinese domains (Figures 3a−c) and ERUS (Figure 3d) in their own domain were large in winter (56−92%). In SCHN, the relative contribution from the neighboring domain (CCHN) was also large (41%). In ERUS, the relative contribution from NCHN was also large (37%). The BaP emitted from NCHN (Figure 3a), CCHN (Figure 3b), and ERUS (Figure 3d) also influenced downwind regions. In the northern part of the SOJ (67%) and JPN (54%), the relative contributions of NCHN were large in winter (Figure 3a). The relative contributions of CCHN to the coastal areas of the Asian Continent in the YEC (71%) were also large (Figure 3b). The ERUS affected the northern part of the SOJ (67%, Figure 3d). In summer, the relative contributions from the three Chinese domains (Figures 3g−i) and ERUS (Figure 3j) to downwind regions decreased. Instead, self-contribution (contribution from its own domain) increased in SKOR (87%, Figure 3k) and JPN (79%, Figure 3l). As shown in Figure S4, the prevailing wind direction is from the south or southeast in the western North Pacific area under the Pacific High. Preventing the transboundary transport of PAH from the Asian continent will cause smaller dry depositions of PAH. In the YEC, the largest contribution was from CCHN (72%). In the SOJ, the relative contributions from NCHN (30%) and ERUS (50%) were large. The relative contributions from NCHN (13%) and ERUS (30%) also influenced the NWP. The contribution from JPN (49%), which is located upwind, also increased in the NWP. G



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During the summer, the predominant wind was from the south or southeast, and the downwind region of the Asian continent was occupied by the Pacific High. Although longrange transport of BaP from the three Chinese and ERUS domains was prevented, the relative contributions from CCHN (Figure 4h) and SCHN (Figure 4i) were large in the downwind and ocean region. Zhang et al.63 revealed that BaP flux of transboundary transport is elevated to 3.5 km and 5 km at 130°E and 140°E, respectively. Considering that the amount of wet deposition is often regarded as column deposition (deposition from higher altitude depending on the cloud height), the larger contributions from CCHN and SCHN would be due to vertical transport of BaP associated with active convection over the Asian continent followed by deposition via precipitation. The relative contributions from the source domain for the three species are similar (Figure 4, Figure S9, Figure S10), because atmospheric mass concentrations, air flow patterns, and precipitation (and thus wet deposition) are the primarily important factors to determine the deposition of the three PAHs. Still, however, as shown in Figure 1 and Figure S3, distribution of WD and of DD of each species is different due to the difference in thermodynamical properties of each PAH. The relative contribution of Chr to downwind regions was larger (approximately 30%) than those of BaP and IcdP. In the atmosphere, it is recognized that 3- and 4-ring PAHs (such as Chr) exist in both the gas and particulate phases depending on the ambient temperature, whereas PAHs with 5 or more rings (such as BaP, IcdP) are existed as the particulate phase. This difference among the species might be due to the vapor−liquid equilibrium, gas−liquid equilibrium, gas−particle (aerosol, ice) interactions, and/or the temperature during long-range transport.

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AUTHOR INFORMATION

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*Phone: +81-76-234-4825; e-mail: [email protected]. ac.jp. ORCID

Yayoi Inomata: 0000-0003-3570-545X Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This research was financially supported by the Environmental Research and Technology Development Fund (Projects B0905, 5-136, and 5-1605) of the Environmental Restoration and Conservation Agency (ERCA), the Grant-in-Aid for Scientific Research (16H05624), and the cooperative research program of Institute of Nature and Environmental Technology, Kanazawa University (JFY2014 No.8). H


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