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Trans-Pacific transport of dust aerosols from East Asia: Insights gained from multiple observations and modeling
Environmental Pollution 230 (2017) 1030e1039
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Trans-Pacific transport of dust aerosols from East Asia: Insights gained from multiple observations and modeling Jianping Guo a, *, Mengyun Lou a, c, Yucong Miao a, **, Yuan Wang b, Zhaoliang Zeng a, Huan Liu a, Jing He a, Hui Xu a, Fu Wang d, Min Min d, Panmao Zhai a a
State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125, USA College of Earth Sciences, University of Chinese Academy of Sciences, Beijing 100049, China d Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites (LRCVES/CMA), National Satellite Meteorological Center, Beijing 100081, China b c
a r t i c l e i n f o
a b s t r a c t
Article history: Received 27 February 2017 Received in revised form 3 July 2017 Accepted 19 July 2017
East Asia is one of the world's largest sources of dust and anthropogenic pollution. Dust particles originating from East Asia have been recognized to travel across the Pacific to North America and beyond, thereby affecting the radiation incident on the surface as well as clouds aloft in the atmosphere. In this study, integrated analyses are performed focusing on one trans-Pacific dust episode during 12e22 March 2015, based on space-borne, ground-based observations, reanalysis data combined with Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT), and the Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem). From the perspective of synoptic patterns, the location and strength of Aleutian low pressure system largely determined the eastward transport of dust plumes towards western North America. Multi-sensor satellite observations reveal that dust aerosols in this episode originated from the Taklimakan and Gobi Deserts. Moreover, the satellite observations suggest that the dust particles can be transformed to polluted particles over the East Asian regions after encountering high concentration of anthropogenic pollutants. In terms of the vertical distribution of polluted dust particles, at the very beginning, they were mainly located in the altitudes ranging from 1 km to 7 km over the source region, then ascended to 2 kme9 km over the Pacific Ocean. The simulations confirm that these elevated dust particles in the lower free troposphere were largely transported along the prevailing westerly jet stream. Overall, observations and modeling demonstrate how a typical springtime dust episode develops and how the dust particles travel over the North Pacific Ocean all the way to North America. © 2017 Elsevier Ltd. All rights reserved.
Keywords: Dust CALIPSO Pacific Transport WRF-Chem PM10 Wet deposition
1. Introduction Dust storms are prevalent in many East Asian regions in spring, including China, South Korea, and Japan (Murayama et al., 2001). Recently, increasing attention has been paid to the trans-Pacific transport of dust originating from East Asia (Uno et al., 2008; Shang et al., 2017) due to its substantial impacts on human health, environment, ecosystems, weather and climate in the downwind areas or even the entire Pacific Ocean (Tegen and Lacis,
* Corresponding author. ** Corresponding author. E-mail addresses: [email protected] (J. Guo), [email protected] (Y. Miao). http://dx.doi.org/10.1016/j.envpol.2017.07.062 0269-7491/© 2017 Elsevier Ltd. All rights reserved.
1996; Prospero, 1999; Kim and Park, 2001; Creamean et al., 2013; Wang et al., 2014; Miao et al., 2015; Guo et al., 2016a). It has been shown that dust storms travelling thousands of kilometers downwind occur approximately two to three times more frequently each spring compared with other seasons (VanCuren and Cahill, 2002). Major eastern Asian dust source regions, including the Taklimakan Desert, Gobi Desert, and Loess Plateau of China, account for ~25% of global dust emissions (Ginoux et al., 2004). After being emitted into the atmosphere, 26% of Asian dust was found to outflow eastward, and roughly 11.5% can be detected in the atmosphere of North America due to trans-Pacific transport (Zhao et al., 2006). Moreover, dust plumes are frequently contaminated by anthropogenic pollutant and biomass smoke over land (J. Huang et al., 2015a). Such an aging process in
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the atmosphere induces significant changes in aerosol properties and alters cloud formation and even global distribution of precipitation (Wang et al., 2013). Hence the global radiation budget and hydrological cycle are susceptible to the long-range transport and transformation of dust aerosols (Feingold et al., 2016). The studies concerning the long-range transport of East Asian dust emerged in the 1980s, when either ground-based observation (e.g., Iwasaka et al., 1983; Murayama et al., 2001) or model simulation (e.g., Nakajima et al., 1989) has been successfully applied. Dust particles are generally ejected to the boundary layer, sometimes up to the free troposphere due to the convection caused by unstable atmospheric conditions (Huang et al., 2008). Therefore, the vertical distribution of dust particles plays a key role in improving our understanding of long-range transport (Guo et al., 2010, 2016b; J. Huang et al., 2015a, Guo et al., 2016b). Additionally, an accurate estimation of the dust climate effect strongly depends on aerosol vertical profiles (e.g., Liao and Seinfeld, 1998). Given the significance of the vertical structure of dust aerosols, Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) (Winker et al., 2010) has been widely applied to investigate the long-range transport of dust (McKendry et al., 2008, Huang et al., 2008; Uno et al., 2008; Guo et al., 2013). Based on the integrated analyses involving satellite and reanalysis data, mid-latitude westerly wind has been recognized as one of the major factors carrying the dust from northwestern China to North America across the Pacific Ocean (e.g., Wilkening et al., 2000; Yu et al., 2012). CALIPSO measurements, combined with aerosol transport models have been extensively used to analyze the trans-Pacific transport of dust (Eguchi et al., 2009). However, few studies regarding the trans-Pacific transport explicitly characterize the dust neighboring source regions over eastern China. Recently, Guo et al. (2016c) suggested that relatively high wind speed and enhanced height of planetary boundary layer (PBL) tend to occur in spring in the northern China, which are favorable for the dust particles to be lofted into the free troposphere. Interestingly, one intensive sand/ dust storm (SDS) episode occurred in northwestern China on 12 March 2015, and then spread throughout eastern China, the Korean Peninsula, Japan, and the western part of North America on 21e22 March 2015. It provides us a golden case to systematically investigate the dust storm formation and its transport route, as well as the underlying physical mechanisms. Therefore, the objective of this work is to elucidate the SDS episode from the perspective of both observations and models and to ultimately shed light on how this episode varies over time and space with a focus on the source regions.
2.1. Satellite observations Because of the lack of surface observations over the Pacific Ocean, the satellite data, including the CALIPSO data and the OMI data, were used to examine this tran-Pacific dust transport event. The CALIPSO satellite was launched on April 2006, which passes over the equator at around 1:30 p.m. and 1:30 a.m. local time (LT). The CALIOP is a primary instrument onboard CALIPSO, and is a dual-wavelength polarization lidar designed to acquire vertical profiles of attenuated backscatter from a near nadir-viewing geometry (Winker et al., 2007). Unlike other space-borne passive satellite sensors, CALIOPSO can detect aerosols both in clear sky conditions and beneath thin cloud layer (Winker et al., 2007; Omar et al., 2009). To identify the dust aloft in the atmosphere, the CALIPSO Level 2 Vertical Feature Mask (VFM) product is used, which has a vertically varying resolution: 30 m below 8.2 km in altitude versus 60 m for the altitudes within 8.2e20.2 km (Winker et al., 2007). The features identified by CALIOP are first classified into aerosol and cloud using a cloud-aerosol discrimination (CAD) algorithm. The level of confidence for the accuracy of aerosol and cloud classification is assessed by a CAD score, which generally ranges from 100 to 0 for aerosol and 0 to 100 for cloud. The larger the CAD value is, the higher confidence we have. When an aerosol layer is identified, the scene classification algorithm further categorizes the aerosol layer to one of the six aerosol types: smoke, polluted continental, polluted dust, dust, clean continental, and clean marine (Z. Liu et al., 2009). Although the accuracy of CALIPSO dust products may be affected by clouds, previous studies (e.g., P. Liu et al., 2009; Amiridis et al., 2013) have proven that these products were good enough to study the large-scale transport of dust. CALIPSO version 3 data used here have significant improvements over previous versions, which have been demonstrated by extensive validation studies (e.g., Kacenelenbogen et al., 2011). Note that CALIOP has better signal-tonoise ratios during nighttime than during daytime due to the noise caused by daytime solar illumination (Z. Liu et al., 2009). Therefore, the entire dust and polluted dust aerosols used in this study refers to those obtained from nighttime CALIOP VFM data unless otherwise noted. In addition, only dust and polluted dust aerosols that meet the criteria described in Table S1 were considered to obtain robust analysis. Based on the CALIOP VFM data, the occurrence/ fractional frequency of dust was calculated to better characterize the vertical structure of dust (Huang et al., 2013). Given most dust particles located in the lower troposphere, only the aerosol features detected below 8.2 km in altitude considered. Therefore, the fractional frequency of dust (or polluted dust) in the ith 30 m vertical bin (fi) can be derived from the following equation:
N fi ¼ Pn i 2. Data and methods Multiple ground-based comprehensive observations, the spaceborne CALIPSO and the Ozone Monitoring Instrument (OMI) measurements, in combination with Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) (Draxler and Rolph, 2013) and the Weather Research and Forecasting Model couple with Chemistry (WRF-Chem) (Grell et al., 2005) were applied to elucidate the trans-Pacific transport of one dust episode, including (1) the general evolutions of this SDS episode based on the OMI and CALIPSO data, and HYSPLIT backward trajectories (section 3.1); (2) the detailed transport processes over source region of SDS episode in East Asia using the surface observations, soundings, and CALIPSO measurements (section 3.2); and (3) the detailed processes over the Pacific Ocean using the WRF-Chem simulations (section 3.3).
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i¼0 Ni
(1)
where Ni is the number of times when dust (or polluted dust) detected by CALIPSO fell in the ith 30 m vertical bin, and n is the total number of 30 m vertical bins. As an active satellite sensor, CALIPSO only makes nadir measurements, resulting in limited spatial coverage (Chen et al., 2002; Vaughan et al., 2009). To compensate for this limitation, the OMI data were used in this study, which has a 2600 km wide swath and provides daily global coverage at a spatial resolution of 13 24 km (Torres et al., 2007). The OMI is a new-generation instrument aboard Aura, mainly designed for measuring ozone. It can also provide daily absorbing aerosol products such as absorbing aerosol index (AAI) (Torres et al., 2007). The AAI can serve as a qualitative indicator of the presence of the absorbing aerosols, such as dust and biomass burning aerosols, even above the clouds, depending on the
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absorbing aerosol concentration (aerosol type) and altitude (AlfaroContreras et al., 2016). Since the dust episode of our interest occurred in March, high AAI value can be thought as high dust loading in the atmosphere. It is noteworthy that both CALIPSO and Aura fly in a sun-synchronous orbit and have an equatorial crossing time of approximately 1:30 p.m. and 1:30 a.m. LT, providing a perfect opportunity to simultaneously observe the dust episodes. 2.2. Meteorological measurements and observations of dust particles As a complement to satellite observations, comprehensive ground-based measurements such as PM2.5 (particulate matter less than 2.5 mm in aerodynamic diameter) and PM10 mass concentration, meteorological records of weather phenomena (e.g., dust storm, floating dust and blowing dust), and soundings were further used to characterize the detailed evolutions of SDS over land from local to regional scales. All of these data were obtained from the National Meteorological Information Center (NMIC), China Meteorological Administration (CMA). The hourly PM10 and PM2.5 mass concentrations at four air quality stations (Table S2) were collected over the potential source regions, including the Kuerle (KEL), Zhangye (ZYS), Zhangjiakou (ZJK), and Yanjin (YJS). In addition, the vertical profiles of temperature and wind collected at four sounding sites (Table S2, and Fig. 1) adjacent to these air quality stations, were used to understand the vertical thermodynamic structures/processes during this SDS episode. The soundings are launched twice a day at 0800 Beijing Time (BJT ¼ UTC þ 8 h) and 2000 BJT. Combined with the vertical distribution of dust particles derived from CALIOP products, the detail processes of this SDS event could be unraveled. The spatial distribution of CALIPSO ground tracks relative to the sounding sites was shown in Fig. 1. A 100 km-radius circle around each sounding site was used to determine the segments of CALIOP measurements used for further analyses. Besides, the dust weather phenomena (i.e., dust storm, floating dust, and blowing dust) recorded at 98 surface meteorological stations across China are used to examine the eastward propagation of dust particles (Goudie and Middleton, 2006). 2.3. Model description and configurations The WRF-Chem model was employed to advance our
understanding the long-range transport processes of dust particles. With respect to the atmospheric chemistry configurations, the RADM2-MADE/SORGAM chemical mechanism (Stockwell et al., 1990) was used. The anthropogenic emissions were set based on the Emissions Database for Global Atmospheric Research (EDGAR) (http://edgar.jrc.ec.europa.eu/). And the emission, transports, mixing, and deposition of dust particles were calculated online following X Huang et al. (2015b). The simulation was conducted from 0000 UTC 10 March (no dust state) to 0000 UTC 23 March 2015, and the first two days were referred to as the spin-up period, and excluded from further analyses. The initial and boundary conditions of meteorology were set by the 6-hourly 1 1 NCEPFNL reanalysis data (https://rda.ucar.edu/datasets/ds083.2/). The target domain (Figs. 2 and 3a) covered the region bounded by 70 E 120 W and 18 N e 70 N with a horizontal grid spacing of 1 1. In the vertical dimension, 48 vertical layers were set from the surface to the 100-hPa level, with resolution varying with altitude. In terms of major physical processes, the parameterization schemes used included the WRF single-moment 5-class microphysics scheme (Hong et al., 2004), the Rapid Radiative Transfer Model for General circulation models (RRTMG) longwave/shortwave scheme (Iacono et al., 2008) with the aerosol direct effect, the Yonsei University (YSU) boundary layer scheme (Hong et al., 2006), the Grell-Freitas cumulus scheme (Grell and Freitas, 2014), and the Noah land surface scheme (Chen and Dudhia, 2001). The air mass backward trajectories were calculated using the NOAA HYSPLIT model, developed by NOAA's Air Resources Laboratory (Draxler and Rolph, 2013). The HYSPLIT is widely used for computing air/pollutant parcel trajectories, as well as the transport, dispersion, chemical transformation, and deposition processes. The trajectories of air/pollutant are calculated based on a hybrid method of the Lagrangian and Eulerian approaches. The Lagrangian approach uses a moving frame of reference for the advection and diffusion calculations as the trajectories or air parcels move from their initial location, whereas Eulerian approach employs a fixed three-dimensional grid as a frame of reference to compute pollutant air concentrations (Stein et al., 2015). The ending points and time of HYSPLT (Table S3) were set according to the region of interest where the dust particles were detected from CALIPSO measurements. As such, the ending points were fallen in two target regions (i.e., the “A” and “B” in Fig. 2). Using the reanalysis data of Global Data Assimilation System (GDAS), eight 216-hr backward trajectories ending at 1300 UTC 21 March 2015 were calculated for
Fig. 1. Spatial distribution of ground-based air quality stations (blue dots), sounding sites (red dots), in combination of the overpassing ground tracks (descending node) of CALIPSO (black slant lines) during the period 12e15 March 2015. The green asterisks represent sources of dust (Guo et al., 2013). The 100 km-radius red circles around the sounding sites are used to determine the segments of along-track CALIPSO measurements. The red rectangle marks the region for cross sections shown in Figs. 9 and 10. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
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Fig. 2. Spatial distribution of OMI/Aura derived absorbing aerosol index showing the temporal evolution of dust episode originating from northeastern Asia. Two target domains were selected for the subsequent backward trajectory and model simulation analyses, one is located at Alaska (66 N, 160 W, red cross symbol A), and another is located at western coastal regions of Canada (57 N, 128 W, red cross symbol B). To highlight the dust episode, only the spatial grids with AAI value greater than 1 were given here. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 3. Spatial distribution of geopotential height (GH) fields and wind vectors at 500-hPa level at 1400 BJT on (a) 12 March, (b) 14 March, (c) 16 March, (d) 18 March, (e) 20 March, and (f) 22 March 2015. The GH fields and wind vectors were derived from NCEP-FNL reanalysis data. The locations of troughs on 12 March and 14 March are marked by the black dash lines in (a) and (b).
the target region “A”, and thirteen 240-hr backward trajectories ending at 1100 UTC 22 March 2015 were made for the target region “B”. 3. Results and discussion 3.1. Multi-sensor satellite observations of trans-Pacific SDS transport and associated synoptic patterns Fig. 2 illustrates the spatial distribution of OMI/Aura derived absorbing aerosol index, which captures the temporal evolution of SDS episode originating from the northeastern Asian regions. The SDS episode initially developed in the Taklimakan Desert (~80 E, 35 N) of northwestern China on 12 March 2015. As shown in Fig. 3a, there was a deep trough developed over the northwest of China on 12 March 2015, which induced strong westerly winds and favored the outbreak of SDS (Aoki et al., 2005). Part of the dust particles could be lifted into the free troposphere, and be transported to the
downwind regions (Fig. 2), forced by the westerly jets between 30 N and 50 N (Fig. 3). On 14 March, the elevated dust particles were transported to the North China Plain (~120 E) (Fig. 2). And during the following seven consecutive days, the elevated dust particles could travel across the northern Pacific Ocean driven by the westerly jets, and reach the North American continent on 21e22 March 2015 (Figs. 2 and 3). During this SDS episode, another synoptic system that should be noted was the Aleutian low-pressure (ALP), which hovered over the northeastern Pacific Ocean between 150 W and 180 W from 16 March to 20 March (Fig. 3c-e). When the elevated dust particles reached the ALP-dominant region, the cyclonic circulation could carry the elevated dust particles to the target regions “A” and “B”. To better understand the tran-Pacific transport process, the vertical curtains of the CALIOP VFM and the backward trajectories of HYSPLIT were shown in Fig. 4. On 12 March, a mass of elevated dust particles could be found over the Taklimakan Desert (~80 E). And then the elevated dust particles were eastwardly advected to
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Fig. 4. Three-dimensional trans-Pacific transport route of the SDS episode. The aerosol vertical curtains were illustrated using CALIPSO nighttime measurements. The red lines are the backward trajectories from the target region “A”, and the blue lines are the backward trajectories from the target region “B”. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 5. Spatial distribution of OMI/Aura derived AAI (shade), overlaid with the weather phenomena (circles) reported by surface stations in East Asia on (a) 12 March, (b) 13 March, (c) 14 March, and (d) 15 March 2015.
the Inner Mongolia (~95 E) on 13 March, and reached the Gobi Desert (~110 E) on 14 March. On 15 March, the dust particles proceeded to the Northeast China and the Korean Peninsula, and then traveled over the Pacific Ocean, and finally reached the North American continent a few days later. This long-range transport process unraveled by the CALIPSO product and HYSPLIT trajectories showed a good agreement with that identified from the OMI data. Interestingly, during this SDS episode, part of the dust particles were marked as polluted dust by the CALIOP VFM products when the dust particles traveled over East Asia from 12 March to 15 March, which may be relevant to the high emissions of anthropogenic pollutants and the aging processes of dust particles (Peng et al., 2016; Miao et al., 2017). Considering that the aging processes of dust particles are extremely complex, which involves heterogeneous reactions of dust particles with gases (Sullivan et al., 2007), condensations of gases (Clarke et al., 2004), coagulations with other types of particles (Chou et al., 2003), and interactions with water vapor (Kim and Park, 2012), it is too hard to use the satellite data alone to investigate the aging processes. Thus, further explicit laboratory studies are warranted to provide better understanding of the aging processes of dust particles (Kim and Park, 2012).
3.2. SDS characterization in East Asia In this section, the ground-based observations, along with the soundings and CALIOP data, were used to further investigate the detailed processes in the potential source regions of East Asia. As illustrated in Fig. 5, the SDS propagation was well manifested by the weather phenomena recorded in the surface stations. On 12 March, the dust events were mainly observed in the northwest of China (Fig. 5a). Two days later, the dust events were found in most stations of eastern China (Fig. 5c). Additionally, the passage of dust plume could cause extremely high aerosol concentration observed at the air quality stations, which was typically characterized by extremely high PM10 concentration (Husar et al., 2001). As illustrated in Fig. 6, the sharp increase of PM10 concentration and decrease of PM2.5/PM10 ratio were first observed at TZS at ~0400 BJT on 13 March, followed by the YZS (~2000 BJT on 13 March), ELH (~1000 BJT on 14 March), and HEB (~1200 BJT on 15 March). Note that both PM2.5 and PM10 concentrations increased significantly during the SDS episode and the increments in PM10 were largely higher than those in PM2.5. On 13 March, the maximum PM10 concentration was found at TZS, which could reach as high as ~7000 mg m3 (Fig. 6a). These sharp
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Fig. 6. Time series of PM2.5 (red curves), PM10 concentration (black curves) and their ratios (PM2.5/PM10, blue curves) during the SDS episode at (a) TZS, (b) YZS, (c) ELH and (d) HEB, spreading from east to west in China. The corresponding red and black horizontal dashed lines represent the average PM2.5 and PM10 concentrations in March 2015, respectively, and two vertical green lines mark the passage of SDS. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
changes of PM10 concentration coincided well with the SDS passage derived from OMI measurements. To further characterize the transport and vertical distribution of the dust particles, the dust fractional frequencies derived from the nighttime CALIOP data were shown in Fig. 7, as well as the observed wind profiles. It was found that the prevailing westerly winds drove the dust particles eastward to the Pacific Ocean. Along the propagation route, at ZYS station, the dust layer were observed at a higher altitude (3.4e5.0 km), compared with other two downwind stations, which may be caused by the local orographic condition. In addition, the vertical profiles of potential temperature (PT) and wind speed at sounding sites of KEL, ZYS, ZJK, YJS before and during the SDS were shown in Fig. S1 of the supplementary materials to unravel the associated local thermodynamics features of PBL during this SDS. The PT profiles varied greatly before and during the SDS for these four sites. At the KEL site, during the SDS the PT profile was generally cooler than that of pervious day (Fig. S1a). In contrast, the PT profile of SDS was almost the same to that of previous day at ZYS (Fig. S1b). Additionally, at ZJK and YJS, no significant difference could be found for the PT profiles below 1 km above ground level (AGL) between the dust day and the previous day (Figs. S1ced); while for the upper level (1e2 km AGL), the PT at ZJK was cooler during the dust episode (Fig. S1c), and that of YJS was warmer (Fig. S1d). In comparison with differing changes of PT profiles at different sites, consistent changes of wind speed profiles could be noted e the winds below ~1 km AGL were significantly stronger during the SDS than in the previous day (Fig. S1). Such a consistent change of wind speed within the PBL indicated that the dynamic factors caused by the large-scale synoptic forcings played an important role in the propagation of SDS. And the responses of thermal structure of PBL were more complex, which may be affected both by the large-scale synoptic forcings and the various local-scale surface forcings.
3.3. Simulated trans-Pacific transport of dust particles Due to the lack of observations over the Pacific Ocean, in this section we used the WRF-Chem outputs to further investigate the detail processes of the tran-Pacific transport of dust particles. Model simulation results (Fig. 8) indicate that the spatial distribution of the elevated dust particles (at the 500-hPa level) was generally consistent with the satellite observations (Fig. 2). The simulated dust particles were most limited to the East Asia before 14 March 2015. With respect to the dust intensity, hotspots were evident over the Taklimakan Desert (~80 E) on 12 March and the Gobi Desert (~110 E) on 14 March (Fig. 8a and b). On 16 March, huge fanlike dust plumes were observed over the Pacific Ocean (Fig. 8c). Beginning from 20 March till 22 March, the persistent pronounced cyclone systems linked to ALP, which was observed to persist over the northeastern Pacific Ocean, facilitated the transport of dust to the two target regions (Figs. 3 and 8). This favorable large-scale synoptic condition resulted in one leading edge of dust plumes reaching Alaska on 20 March and another west coast of Canada on 22 March. Altitude-longitude cross sections (Fig. 9) averaged over the belt of 30 N - 55 N revealed that the dust plume can be elevated to the height of ~3e5 km above sea level (ASL) over the source regions forced by orographic conditions. By and large, the simulated heights of the dust plumes agreed well with those as observed by the CALIOP (Fig. 4). As illustrated in Fig. 4b, on 14 March 2015 there was a trough developed over the eastern China at 550-hPa level, which would induce upward motions (Fig. S2b) and carry the dust particles produced in the boundary layer to the free troposphere (Fig. 9b), and part of dust particles could be lifted to an altitude as high as 8 km. Combining Figs. 9 and 10, it can be clearly seen that during the tran-Pacific transport process, part of dust parties were well above the underlying stratocumulus or stratus clouds over northern Pacific Ocean. As a result, although most of dust particles were removed through the dry and wet deposition processes, most
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Fig. 7. Vertical profiles of fractional frequency of (a) pure dust and (b) polluted dust derived from CALIOP nighttime data from 12 March to 15 March 2015, along with the observed wind profiles. The horizontal black line represents the terrain height of each site. Top 1% (red dotted line) means the highest height where the fractional frequency is no less than 99%. Bottom 1% (green dotted line) means the lowest height where the fractional frequency is no more than 1%. The sampling locations of CALIOP data and sounding sites are marked in Fig. 1. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 8. Spatial distributions of WRF-Chem simulated dust concentration and wind vector field at 500-hPa level at 1400 BJT on (a) 12 March, (b) 14 March, (c) 16 March, (d) 18 March, (e) 20 March, and (f) 22 March 2015. The red dash lines mark the regions (30 N-55 N) of cross sections shown in Figs. 9 and 10. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
of which occurred in the downwind regions nearest to dust sources in eastern Asia (Fig. S3), the rest of elevated small dust particles can travel across the Pacific Ocean under the favorable synoptic conditions (Figs. 2 and 8).
4. Conclusions In this paper, multiple observational data, including groundbased PM2.5 and PM10 concentrations, weather phenomena
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Fig. 9. Vertical cross sections of WRF-Chem simulated dust concentration and wind vector field averaged along the belt of 30 N to 55 N (denoted by the two horizontal parallel dashed lines in Fig. 8) at 1400 BJT on (a) 12 March, (b) 14 March, (c) 16 March, (d) 18 March, (e) 20 March, and (f) 22 March 2015. Note that the vertical velocity is multiplied by a factor of 30 to enhance the visual interpretation when plotting wind vectors.
Fig. 10. Similar as Fig. 9, but for the vertical cross sections of WRF-Chem simulated cloud water mixing ratio.
record, atmospheric soundings, space-borne dust measurements from CALIOP/CALIPSO and OMI/Aura, in combination of the HYSPLIT model, and WRF-Chem model were comprehensively examined to characterize a dust episode in spring of 2015. Over the source region, pervasive dust plumes were found over the Taklimakan Desert and Gobi Desert at the initial phase (12e14 March 2015) by simultaneous measurements of CALIOP/CALIPSO and OMI/Aura. Further, ground-based weather observations, along with PM10 concentration and PM2.5/PM10 ratio, revealed the temporal evolution of the SDS episode. Satellite data also identified the quick transition of dust to polluted dust in the East Asia. Beyond the continental region, almost no ground-based observations are
available over the Pacific Ocean. To fill in the data gap, the unique capability of CALIOP in providing the vertical distribution of dust particles offered us the unique opportunity to be able to seamlessly monitor the evolution of dust episode. Combining multiple observations and explicit modeling simulation, the physical mechanism underlying the long-range transport of dust episode has been put forward: In the dust source region, upon the dust particles were uplifted into free troposphere as evident in CALIOP measurements and the WRF-Chem simulations. Over the Pacific Ocean, the prevailing westerly winds (at high altitudes) in northern hemisphere, on one hand, tend to keep the dust plume well above the underlying stratocumulus or stratus
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clouds over Pacific Ocean, making it being devoid of dry and wet deposition. In particular, the Aleutian cyclonic circulation over northern Pacific Ocean further carried dust plumes eastward to Alaska and western coastal region of Canada on 20 March 20, and 22 March, respectively. All of the abovementioned processes facilitate the long-range transport of dust plumes. As a first step in a series of efforts, integrated analyses based on multi-source observations and process-level model simulation have been applied in attempt to shed light on physical details in one individual SDS episode over time and space. This work has significant implications for long-range transport studies over other regions affected by dust or anthropogenic aerosols, although future observational and modeling work are warranted in order to assess the long-term climatological features regarding trans-Pacific transport of SDS, let alone the complicated interactions between dust aerosols and clouds during the transport processes. Acknowledgements This work was supported by the National Natural Science Foundation of China under Grants 41471301 and 91544217, the Ministry of Science and Technology under Grant 2017YFA0603501, Central Leading Local Development of Science and Technology Project in China under Grant HN 2016-149, the Climate Change Project of China Meteorological Administration (CMA) under Grant CCSF201732, and Chinese Academy of Meteorological Sciences under Grants 2017Z005, 2017Y002 and 2017R001. The PM2.5/PM10 and radiosonde data used in this paper were acquired from China Meteorological Administration, whereas the OMI/Aura and CALIOP/ CALIPSO data were obtained from NASA. The authors appreciate very much the NASA team for providing the reliable data used in this study. Last but not least, we are grateful to the editor and the four anonymous reviewers for their constructive comments, which help significantly improve the quality of this manuscript. Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.envpol.2017.07.062. References Alfaro-Contreras, R., Zhang, J., Campbell, J.R., Reid, J.S., 2016. Investigating the frequency and interannual variability in global above-cloud aerosol characteristics with CALIOP and OMI. Atmos. Chem. Phys. 16, 47e69. http://dx.doi.org/10.5194/ acp-16-47-2016. Amiridis, V., Wandinger, U., Marinou, E., Giannakaki, E., Tsekeri, A., Basart, S., Kazadzis, S., Gkikas, A., Taylor, M., Baldasano, J.M., Ansmann, A., 2013. Optimizing CALIPSO Saharan dust retrievals. Atmos. Chem. Phys. 13, 12089e12106. http://dx.doi.org/10.5194/acp-13-12089-2013, 14749-14795. Aoki, I., Kurosaki, Y., Osada, R., Sato, T., Kimura, F., 2005. Dust storms generated by mesoscale cold fronts in the Tarim Basin, Northwest China. Geophys. Res. Lett. 32 http://dx.doi.org/10.1029/2004GL021776. Chen, F., Dudhia, J., 2001. Coupling an advanced land surfaceehydrology model with the penn stateeNCAR MM5 modeling system. Part I: model implementation and sensitivity. Mon. Weather Rev. 129, 569e585. http://dx.doi.org/10.1175/ 1520-0493(2001)129<0587:CAALSH>2.0.CO;2. Chen, Z., Torres, O., McCormick, M.P., Smith, W., Ahn, C., 2002. Comparative study of aerosol and cloud detected by CALIPSO and OMI. Atmos. Environ. 51, 187e195. http://dx.doi.org/10.1016/j.atmosenv.2012.01.024. Chou, C.C.K., Chen, T.K., Huang, S.H., Liu, S.C., 2003. Radiative absorption capability of asian dust with black carbon contamination. Geophys. Res. Lett. 30 (12), 18e21. Clarke, A.D., Shinozuka, Y., Kapustin, V.N., Howell, S., Huebert, B., Doherty, S., Anderson, T., Covert, D., Anderson, J., Hua, X., Moore II, K.G., McNaughton, C., Carmichael, G., 2004. Size distributions and mixtures of dust and black carbon aerosol in asian outflow: physiochemistry and optical properties. J. Geophys. Res.- Atmos. 109 (15). D15S09 1e20. Creamean, J.M., Suski, K.J., Rosenfeld, D., Cazorla, A., DeMott, P.J., Sullivan, R.C., White, A.B., Ralph, F.M., Minnis, P., Comstock, J.M., Tomlinson, J.M., Prather, K.A., 2013. Dust and biological aerosols from the Sahara and Asia influence precipitation in the western U.S. Science 339, 1572e1578. http://dx.doi.org/10.1126/
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Trans-Pacific transport of dust aerosols from East Asia: Insights gained from multiple observations and modeling Jianping Guo a, *, Mengyun Lou a, c, Yucong Miao a, **, Yuan Wang b, Zhaoliang Zeng a, Huan Liu a, Jing He a, Hui Xu a, Fu Wang d, Min Min d, Panmao Zhai a a
State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125, USA College of Earth Sciences, University of Chinese Academy of Sciences, Beijing 100049, China d Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites (LRCVES/CMA), National Satellite Meteorological Center, Beijing 100081, China b c
a r t i c l e i n f o
a b s t r a c t
Article history: Received 27 February 2017 Received in revised form 3 July 2017 Accepted 19 July 2017
East Asia is one of the world's largest sources of dust and anthropogenic pollution. Dust particles originating from East Asia have been recognized to travel across the Pacific to North America and beyond, thereby affecting the radiation incident on the surface as well as clouds aloft in the atmosphere. In this study, integrated analyses are performed focusing on one trans-Pacific dust episode during 12e22 March 2015, based on space-borne, ground-based observations, reanalysis data combined with Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT), and the Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem). From the perspective of synoptic patterns, the location and strength of Aleutian low pressure system largely determined the eastward transport of dust plumes towards western North America. Multi-sensor satellite observations reveal that dust aerosols in this episode originated from the Taklimakan and Gobi Deserts. Moreover, the satellite observations suggest that the dust particles can be transformed to polluted particles over the East Asian regions after encountering high concentration of anthropogenic pollutants. In terms of the vertical distribution of polluted dust particles, at the very beginning, they were mainly located in the altitudes ranging from 1 km to 7 km over the source region, then ascended to 2 kme9 km over the Pacific Ocean. The simulations confirm that these elevated dust particles in the lower free troposphere were largely transported along the prevailing westerly jet stream. Overall, observations and modeling demonstrate how a typical springtime dust episode develops and how the dust particles travel over the North Pacific Ocean all the way to North America. © 2017 Elsevier Ltd. All rights reserved.
Keywords: Dust CALIPSO Pacific Transport WRF-Chem PM10 Wet deposition
1. Introduction Dust storms are prevalent in many East Asian regions in spring, including China, South Korea, and Japan (Murayama et al., 2001). Recently, increasing attention has been paid to the trans-Pacific transport of dust originating from East Asia (Uno et al., 2008; Shang et al., 2017) due to its substantial impacts on human health, environment, ecosystems, weather and climate in the downwind areas or even the entire Pacific Ocean (Tegen and Lacis,
* Corresponding author. ** Corresponding author. E-mail addresses: [email protected] (J. Guo), [email protected] (Y. Miao). http://dx.doi.org/10.1016/j.envpol.2017.07.062 0269-7491/© 2017 Elsevier Ltd. All rights reserved.
1996; Prospero, 1999; Kim and Park, 2001; Creamean et al., 2013; Wang et al., 2014; Miao et al., 2015; Guo et al., 2016a). It has been shown that dust storms travelling thousands of kilometers downwind occur approximately two to three times more frequently each spring compared with other seasons (VanCuren and Cahill, 2002). Major eastern Asian dust source regions, including the Taklimakan Desert, Gobi Desert, and Loess Plateau of China, account for ~25% of global dust emissions (Ginoux et al., 2004). After being emitted into the atmosphere, 26% of Asian dust was found to outflow eastward, and roughly 11.5% can be detected in the atmosphere of North America due to trans-Pacific transport (Zhao et al., 2006). Moreover, dust plumes are frequently contaminated by anthropogenic pollutant and biomass smoke over land (J. Huang et al., 2015a). Such an aging process in
J. Guo et al. / Environmental Pollution 230 (2017) 1030e1039
the atmosphere induces significant changes in aerosol properties and alters cloud formation and even global distribution of precipitation (Wang et al., 2013). Hence the global radiation budget and hydrological cycle are susceptible to the long-range transport and transformation of dust aerosols (Feingold et al., 2016). The studies concerning the long-range transport of East Asian dust emerged in the 1980s, when either ground-based observation (e.g., Iwasaka et al., 1983; Murayama et al., 2001) or model simulation (e.g., Nakajima et al., 1989) has been successfully applied. Dust particles are generally ejected to the boundary layer, sometimes up to the free troposphere due to the convection caused by unstable atmospheric conditions (Huang et al., 2008). Therefore, the vertical distribution of dust particles plays a key role in improving our understanding of long-range transport (Guo et al., 2010, 2016b; J. Huang et al., 2015a, Guo et al., 2016b). Additionally, an accurate estimation of the dust climate effect strongly depends on aerosol vertical profiles (e.g., Liao and Seinfeld, 1998). Given the significance of the vertical structure of dust aerosols, Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) (Winker et al., 2010) has been widely applied to investigate the long-range transport of dust (McKendry et al., 2008, Huang et al., 2008; Uno et al., 2008; Guo et al., 2013). Based on the integrated analyses involving satellite and reanalysis data, mid-latitude westerly wind has been recognized as one of the major factors carrying the dust from northwestern China to North America across the Pacific Ocean (e.g., Wilkening et al., 2000; Yu et al., 2012). CALIPSO measurements, combined with aerosol transport models have been extensively used to analyze the trans-Pacific transport of dust (Eguchi et al., 2009). However, few studies regarding the trans-Pacific transport explicitly characterize the dust neighboring source regions over eastern China. Recently, Guo et al. (2016c) suggested that relatively high wind speed and enhanced height of planetary boundary layer (PBL) tend to occur in spring in the northern China, which are favorable for the dust particles to be lofted into the free troposphere. Interestingly, one intensive sand/ dust storm (SDS) episode occurred in northwestern China on 12 March 2015, and then spread throughout eastern China, the Korean Peninsula, Japan, and the western part of North America on 21e22 March 2015. It provides us a golden case to systematically investigate the dust storm formation and its transport route, as well as the underlying physical mechanisms. Therefore, the objective of this work is to elucidate the SDS episode from the perspective of both observations and models and to ultimately shed light on how this episode varies over time and space with a focus on the source regions.
2.1. Satellite observations Because of the lack of surface observations over the Pacific Ocean, the satellite data, including the CALIPSO data and the OMI data, were used to examine this tran-Pacific dust transport event. The CALIPSO satellite was launched on April 2006, which passes over the equator at around 1:30 p.m. and 1:30 a.m. local time (LT). The CALIOP is a primary instrument onboard CALIPSO, and is a dual-wavelength polarization lidar designed to acquire vertical profiles of attenuated backscatter from a near nadir-viewing geometry (Winker et al., 2007). Unlike other space-borne passive satellite sensors, CALIOPSO can detect aerosols both in clear sky conditions and beneath thin cloud layer (Winker et al., 2007; Omar et al., 2009). To identify the dust aloft in the atmosphere, the CALIPSO Level 2 Vertical Feature Mask (VFM) product is used, which has a vertically varying resolution: 30 m below 8.2 km in altitude versus 60 m for the altitudes within 8.2e20.2 km (Winker et al., 2007). The features identified by CALIOP are first classified into aerosol and cloud using a cloud-aerosol discrimination (CAD) algorithm. The level of confidence for the accuracy of aerosol and cloud classification is assessed by a CAD score, which generally ranges from 100 to 0 for aerosol and 0 to 100 for cloud. The larger the CAD value is, the higher confidence we have. When an aerosol layer is identified, the scene classification algorithm further categorizes the aerosol layer to one of the six aerosol types: smoke, polluted continental, polluted dust, dust, clean continental, and clean marine (Z. Liu et al., 2009). Although the accuracy of CALIPSO dust products may be affected by clouds, previous studies (e.g., P. Liu et al., 2009; Amiridis et al., 2013) have proven that these products were good enough to study the large-scale transport of dust. CALIPSO version 3 data used here have significant improvements over previous versions, which have been demonstrated by extensive validation studies (e.g., Kacenelenbogen et al., 2011). Note that CALIOP has better signal-tonoise ratios during nighttime than during daytime due to the noise caused by daytime solar illumination (Z. Liu et al., 2009). Therefore, the entire dust and polluted dust aerosols used in this study refers to those obtained from nighttime CALIOP VFM data unless otherwise noted. In addition, only dust and polluted dust aerosols that meet the criteria described in Table S1 were considered to obtain robust analysis. Based on the CALIOP VFM data, the occurrence/ fractional frequency of dust was calculated to better characterize the vertical structure of dust (Huang et al., 2013). Given most dust particles located in the lower troposphere, only the aerosol features detected below 8.2 km in altitude considered. Therefore, the fractional frequency of dust (or polluted dust) in the ith 30 m vertical bin (fi) can be derived from the following equation:
N fi ¼ Pn i 2. Data and methods Multiple ground-based comprehensive observations, the spaceborne CALIPSO and the Ozone Monitoring Instrument (OMI) measurements, in combination with Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) (Draxler and Rolph, 2013) and the Weather Research and Forecasting Model couple with Chemistry (WRF-Chem) (Grell et al., 2005) were applied to elucidate the trans-Pacific transport of one dust episode, including (1) the general evolutions of this SDS episode based on the OMI and CALIPSO data, and HYSPLIT backward trajectories (section 3.1); (2) the detailed transport processes over source region of SDS episode in East Asia using the surface observations, soundings, and CALIPSO measurements (section 3.2); and (3) the detailed processes over the Pacific Ocean using the WRF-Chem simulations (section 3.3).
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i¼0 Ni
(1)
where Ni is the number of times when dust (or polluted dust) detected by CALIPSO fell in the ith 30 m vertical bin, and n is the total number of 30 m vertical bins. As an active satellite sensor, CALIPSO only makes nadir measurements, resulting in limited spatial coverage (Chen et al., 2002; Vaughan et al., 2009). To compensate for this limitation, the OMI data were used in this study, which has a 2600 km wide swath and provides daily global coverage at a spatial resolution of 13 24 km (Torres et al., 2007). The OMI is a new-generation instrument aboard Aura, mainly designed for measuring ozone. It can also provide daily absorbing aerosol products such as absorbing aerosol index (AAI) (Torres et al., 2007). The AAI can serve as a qualitative indicator of the presence of the absorbing aerosols, such as dust and biomass burning aerosols, even above the clouds, depending on the
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absorbing aerosol concentration (aerosol type) and altitude (AlfaroContreras et al., 2016). Since the dust episode of our interest occurred in March, high AAI value can be thought as high dust loading in the atmosphere. It is noteworthy that both CALIPSO and Aura fly in a sun-synchronous orbit and have an equatorial crossing time of approximately 1:30 p.m. and 1:30 a.m. LT, providing a perfect opportunity to simultaneously observe the dust episodes. 2.2. Meteorological measurements and observations of dust particles As a complement to satellite observations, comprehensive ground-based measurements such as PM2.5 (particulate matter less than 2.5 mm in aerodynamic diameter) and PM10 mass concentration, meteorological records of weather phenomena (e.g., dust storm, floating dust and blowing dust), and soundings were further used to characterize the detailed evolutions of SDS over land from local to regional scales. All of these data were obtained from the National Meteorological Information Center (NMIC), China Meteorological Administration (CMA). The hourly PM10 and PM2.5 mass concentrations at four air quality stations (Table S2) were collected over the potential source regions, including the Kuerle (KEL), Zhangye (ZYS), Zhangjiakou (ZJK), and Yanjin (YJS). In addition, the vertical profiles of temperature and wind collected at four sounding sites (Table S2, and Fig. 1) adjacent to these air quality stations, were used to understand the vertical thermodynamic structures/processes during this SDS episode. The soundings are launched twice a day at 0800 Beijing Time (BJT ¼ UTC þ 8 h) and 2000 BJT. Combined with the vertical distribution of dust particles derived from CALIOP products, the detail processes of this SDS event could be unraveled. The spatial distribution of CALIPSO ground tracks relative to the sounding sites was shown in Fig. 1. A 100 km-radius circle around each sounding site was used to determine the segments of CALIOP measurements used for further analyses. Besides, the dust weather phenomena (i.e., dust storm, floating dust, and blowing dust) recorded at 98 surface meteorological stations across China are used to examine the eastward propagation of dust particles (Goudie and Middleton, 2006). 2.3. Model description and configurations The WRF-Chem model was employed to advance our
understanding the long-range transport processes of dust particles. With respect to the atmospheric chemistry configurations, the RADM2-MADE/SORGAM chemical mechanism (Stockwell et al., 1990) was used. The anthropogenic emissions were set based on the Emissions Database for Global Atmospheric Research (EDGAR) (http://edgar.jrc.ec.europa.eu/). And the emission, transports, mixing, and deposition of dust particles were calculated online following X Huang et al. (2015b). The simulation was conducted from 0000 UTC 10 March (no dust state) to 0000 UTC 23 March 2015, and the first two days were referred to as the spin-up period, and excluded from further analyses. The initial and boundary conditions of meteorology were set by the 6-hourly 1 1 NCEPFNL reanalysis data (https://rda.ucar.edu/datasets/ds083.2/). The target domain (Figs. 2 and 3a) covered the region bounded by 70 E 120 W and 18 N e 70 N with a horizontal grid spacing of 1 1. In the vertical dimension, 48 vertical layers were set from the surface to the 100-hPa level, with resolution varying with altitude. In terms of major physical processes, the parameterization schemes used included the WRF single-moment 5-class microphysics scheme (Hong et al., 2004), the Rapid Radiative Transfer Model for General circulation models (RRTMG) longwave/shortwave scheme (Iacono et al., 2008) with the aerosol direct effect, the Yonsei University (YSU) boundary layer scheme (Hong et al., 2006), the Grell-Freitas cumulus scheme (Grell and Freitas, 2014), and the Noah land surface scheme (Chen and Dudhia, 2001). The air mass backward trajectories were calculated using the NOAA HYSPLIT model, developed by NOAA's Air Resources Laboratory (Draxler and Rolph, 2013). The HYSPLIT is widely used for computing air/pollutant parcel trajectories, as well as the transport, dispersion, chemical transformation, and deposition processes. The trajectories of air/pollutant are calculated based on a hybrid method of the Lagrangian and Eulerian approaches. The Lagrangian approach uses a moving frame of reference for the advection and diffusion calculations as the trajectories or air parcels move from their initial location, whereas Eulerian approach employs a fixed three-dimensional grid as a frame of reference to compute pollutant air concentrations (Stein et al., 2015). The ending points and time of HYSPLT (Table S3) were set according to the region of interest where the dust particles were detected from CALIPSO measurements. As such, the ending points were fallen in two target regions (i.e., the “A” and “B” in Fig. 2). Using the reanalysis data of Global Data Assimilation System (GDAS), eight 216-hr backward trajectories ending at 1300 UTC 21 March 2015 were calculated for
Fig. 1. Spatial distribution of ground-based air quality stations (blue dots), sounding sites (red dots), in combination of the overpassing ground tracks (descending node) of CALIPSO (black slant lines) during the period 12e15 March 2015. The green asterisks represent sources of dust (Guo et al., 2013). The 100 km-radius red circles around the sounding sites are used to determine the segments of along-track CALIPSO measurements. The red rectangle marks the region for cross sections shown in Figs. 9 and 10. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
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Fig. 2. Spatial distribution of OMI/Aura derived absorbing aerosol index showing the temporal evolution of dust episode originating from northeastern Asia. Two target domains were selected for the subsequent backward trajectory and model simulation analyses, one is located at Alaska (66 N, 160 W, red cross symbol A), and another is located at western coastal regions of Canada (57 N, 128 W, red cross symbol B). To highlight the dust episode, only the spatial grids with AAI value greater than 1 were given here. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 3. Spatial distribution of geopotential height (GH) fields and wind vectors at 500-hPa level at 1400 BJT on (a) 12 March, (b) 14 March, (c) 16 March, (d) 18 March, (e) 20 March, and (f) 22 March 2015. The GH fields and wind vectors were derived from NCEP-FNL reanalysis data. The locations of troughs on 12 March and 14 March are marked by the black dash lines in (a) and (b).
the target region “A”, and thirteen 240-hr backward trajectories ending at 1100 UTC 22 March 2015 were made for the target region “B”. 3. Results and discussion 3.1. Multi-sensor satellite observations of trans-Pacific SDS transport and associated synoptic patterns Fig. 2 illustrates the spatial distribution of OMI/Aura derived absorbing aerosol index, which captures the temporal evolution of SDS episode originating from the northeastern Asian regions. The SDS episode initially developed in the Taklimakan Desert (~80 E, 35 N) of northwestern China on 12 March 2015. As shown in Fig. 3a, there was a deep trough developed over the northwest of China on 12 March 2015, which induced strong westerly winds and favored the outbreak of SDS (Aoki et al., 2005). Part of the dust particles could be lifted into the free troposphere, and be transported to the
downwind regions (Fig. 2), forced by the westerly jets between 30 N and 50 N (Fig. 3). On 14 March, the elevated dust particles were transported to the North China Plain (~120 E) (Fig. 2). And during the following seven consecutive days, the elevated dust particles could travel across the northern Pacific Ocean driven by the westerly jets, and reach the North American continent on 21e22 March 2015 (Figs. 2 and 3). During this SDS episode, another synoptic system that should be noted was the Aleutian low-pressure (ALP), which hovered over the northeastern Pacific Ocean between 150 W and 180 W from 16 March to 20 March (Fig. 3c-e). When the elevated dust particles reached the ALP-dominant region, the cyclonic circulation could carry the elevated dust particles to the target regions “A” and “B”. To better understand the tran-Pacific transport process, the vertical curtains of the CALIOP VFM and the backward trajectories of HYSPLIT were shown in Fig. 4. On 12 March, a mass of elevated dust particles could be found over the Taklimakan Desert (~80 E). And then the elevated dust particles were eastwardly advected to
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Fig. 4. Three-dimensional trans-Pacific transport route of the SDS episode. The aerosol vertical curtains were illustrated using CALIPSO nighttime measurements. The red lines are the backward trajectories from the target region “A”, and the blue lines are the backward trajectories from the target region “B”. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 5. Spatial distribution of OMI/Aura derived AAI (shade), overlaid with the weather phenomena (circles) reported by surface stations in East Asia on (a) 12 March, (b) 13 March, (c) 14 March, and (d) 15 March 2015.
the Inner Mongolia (~95 E) on 13 March, and reached the Gobi Desert (~110 E) on 14 March. On 15 March, the dust particles proceeded to the Northeast China and the Korean Peninsula, and then traveled over the Pacific Ocean, and finally reached the North American continent a few days later. This long-range transport process unraveled by the CALIPSO product and HYSPLIT trajectories showed a good agreement with that identified from the OMI data. Interestingly, during this SDS episode, part of the dust particles were marked as polluted dust by the CALIOP VFM products when the dust particles traveled over East Asia from 12 March to 15 March, which may be relevant to the high emissions of anthropogenic pollutants and the aging processes of dust particles (Peng et al., 2016; Miao et al., 2017). Considering that the aging processes of dust particles are extremely complex, which involves heterogeneous reactions of dust particles with gases (Sullivan et al., 2007), condensations of gases (Clarke et al., 2004), coagulations with other types of particles (Chou et al., 2003), and interactions with water vapor (Kim and Park, 2012), it is too hard to use the satellite data alone to investigate the aging processes. Thus, further explicit laboratory studies are warranted to provide better understanding of the aging processes of dust particles (Kim and Park, 2012).
3.2. SDS characterization in East Asia In this section, the ground-based observations, along with the soundings and CALIOP data, were used to further investigate the detailed processes in the potential source regions of East Asia. As illustrated in Fig. 5, the SDS propagation was well manifested by the weather phenomena recorded in the surface stations. On 12 March, the dust events were mainly observed in the northwest of China (Fig. 5a). Two days later, the dust events were found in most stations of eastern China (Fig. 5c). Additionally, the passage of dust plume could cause extremely high aerosol concentration observed at the air quality stations, which was typically characterized by extremely high PM10 concentration (Husar et al., 2001). As illustrated in Fig. 6, the sharp increase of PM10 concentration and decrease of PM2.5/PM10 ratio were first observed at TZS at ~0400 BJT on 13 March, followed by the YZS (~2000 BJT on 13 March), ELH (~1000 BJT on 14 March), and HEB (~1200 BJT on 15 March). Note that both PM2.5 and PM10 concentrations increased significantly during the SDS episode and the increments in PM10 were largely higher than those in PM2.5. On 13 March, the maximum PM10 concentration was found at TZS, which could reach as high as ~7000 mg m3 (Fig. 6a). These sharp
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Fig. 6. Time series of PM2.5 (red curves), PM10 concentration (black curves) and their ratios (PM2.5/PM10, blue curves) during the SDS episode at (a) TZS, (b) YZS, (c) ELH and (d) HEB, spreading from east to west in China. The corresponding red and black horizontal dashed lines represent the average PM2.5 and PM10 concentrations in March 2015, respectively, and two vertical green lines mark the passage of SDS. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
changes of PM10 concentration coincided well with the SDS passage derived from OMI measurements. To further characterize the transport and vertical distribution of the dust particles, the dust fractional frequencies derived from the nighttime CALIOP data were shown in Fig. 7, as well as the observed wind profiles. It was found that the prevailing westerly winds drove the dust particles eastward to the Pacific Ocean. Along the propagation route, at ZYS station, the dust layer were observed at a higher altitude (3.4e5.0 km), compared with other two downwind stations, which may be caused by the local orographic condition. In addition, the vertical profiles of potential temperature (PT) and wind speed at sounding sites of KEL, ZYS, ZJK, YJS before and during the SDS were shown in Fig. S1 of the supplementary materials to unravel the associated local thermodynamics features of PBL during this SDS. The PT profiles varied greatly before and during the SDS for these four sites. At the KEL site, during the SDS the PT profile was generally cooler than that of pervious day (Fig. S1a). In contrast, the PT profile of SDS was almost the same to that of previous day at ZYS (Fig. S1b). Additionally, at ZJK and YJS, no significant difference could be found for the PT profiles below 1 km above ground level (AGL) between the dust day and the previous day (Figs. S1ced); while for the upper level (1e2 km AGL), the PT at ZJK was cooler during the dust episode (Fig. S1c), and that of YJS was warmer (Fig. S1d). In comparison with differing changes of PT profiles at different sites, consistent changes of wind speed profiles could be noted e the winds below ~1 km AGL were significantly stronger during the SDS than in the previous day (Fig. S1). Such a consistent change of wind speed within the PBL indicated that the dynamic factors caused by the large-scale synoptic forcings played an important role in the propagation of SDS. And the responses of thermal structure of PBL were more complex, which may be affected both by the large-scale synoptic forcings and the various local-scale surface forcings.
3.3. Simulated trans-Pacific transport of dust particles Due to the lack of observations over the Pacific Ocean, in this section we used the WRF-Chem outputs to further investigate the detail processes of the tran-Pacific transport of dust particles. Model simulation results (Fig. 8) indicate that the spatial distribution of the elevated dust particles (at the 500-hPa level) was generally consistent with the satellite observations (Fig. 2). The simulated dust particles were most limited to the East Asia before 14 March 2015. With respect to the dust intensity, hotspots were evident over the Taklimakan Desert (~80 E) on 12 March and the Gobi Desert (~110 E) on 14 March (Fig. 8a and b). On 16 March, huge fanlike dust plumes were observed over the Pacific Ocean (Fig. 8c). Beginning from 20 March till 22 March, the persistent pronounced cyclone systems linked to ALP, which was observed to persist over the northeastern Pacific Ocean, facilitated the transport of dust to the two target regions (Figs. 3 and 8). This favorable large-scale synoptic condition resulted in one leading edge of dust plumes reaching Alaska on 20 March and another west coast of Canada on 22 March. Altitude-longitude cross sections (Fig. 9) averaged over the belt of 30 N - 55 N revealed that the dust plume can be elevated to the height of ~3e5 km above sea level (ASL) over the source regions forced by orographic conditions. By and large, the simulated heights of the dust plumes agreed well with those as observed by the CALIOP (Fig. 4). As illustrated in Fig. 4b, on 14 March 2015 there was a trough developed over the eastern China at 550-hPa level, which would induce upward motions (Fig. S2b) and carry the dust particles produced in the boundary layer to the free troposphere (Fig. 9b), and part of dust particles could be lifted to an altitude as high as 8 km. Combining Figs. 9 and 10, it can be clearly seen that during the tran-Pacific transport process, part of dust parties were well above the underlying stratocumulus or stratus clouds over northern Pacific Ocean. As a result, although most of dust particles were removed through the dry and wet deposition processes, most
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Fig. 7. Vertical profiles of fractional frequency of (a) pure dust and (b) polluted dust derived from CALIOP nighttime data from 12 March to 15 March 2015, along with the observed wind profiles. The horizontal black line represents the terrain height of each site. Top 1% (red dotted line) means the highest height where the fractional frequency is no less than 99%. Bottom 1% (green dotted line) means the lowest height where the fractional frequency is no more than 1%. The sampling locations of CALIOP data and sounding sites are marked in Fig. 1. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 8. Spatial distributions of WRF-Chem simulated dust concentration and wind vector field at 500-hPa level at 1400 BJT on (a) 12 March, (b) 14 March, (c) 16 March, (d) 18 March, (e) 20 March, and (f) 22 March 2015. The red dash lines mark the regions (30 N-55 N) of cross sections shown in Figs. 9 and 10. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
of which occurred in the downwind regions nearest to dust sources in eastern Asia (Fig. S3), the rest of elevated small dust particles can travel across the Pacific Ocean under the favorable synoptic conditions (Figs. 2 and 8).
4. Conclusions In this paper, multiple observational data, including groundbased PM2.5 and PM10 concentrations, weather phenomena
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Fig. 9. Vertical cross sections of WRF-Chem simulated dust concentration and wind vector field averaged along the belt of 30 N to 55 N (denoted by the two horizontal parallel dashed lines in Fig. 8) at 1400 BJT on (a) 12 March, (b) 14 March, (c) 16 March, (d) 18 March, (e) 20 March, and (f) 22 March 2015. Note that the vertical velocity is multiplied by a factor of 30 to enhance the visual interpretation when plotting wind vectors.
Fig. 10. Similar as Fig. 9, but for the vertical cross sections of WRF-Chem simulated cloud water mixing ratio.
record, atmospheric soundings, space-borne dust measurements from CALIOP/CALIPSO and OMI/Aura, in combination of the HYSPLIT model, and WRF-Chem model were comprehensively examined to characterize a dust episode in spring of 2015. Over the source region, pervasive dust plumes were found over the Taklimakan Desert and Gobi Desert at the initial phase (12e14 March 2015) by simultaneous measurements of CALIOP/CALIPSO and OMI/Aura. Further, ground-based weather observations, along with PM10 concentration and PM2.5/PM10 ratio, revealed the temporal evolution of the SDS episode. Satellite data also identified the quick transition of dust to polluted dust in the East Asia. Beyond the continental region, almost no ground-based observations are
available over the Pacific Ocean. To fill in the data gap, the unique capability of CALIOP in providing the vertical distribution of dust particles offered us the unique opportunity to be able to seamlessly monitor the evolution of dust episode. Combining multiple observations and explicit modeling simulation, the physical mechanism underlying the long-range transport of dust episode has been put forward: In the dust source region, upon the dust particles were uplifted into free troposphere as evident in CALIOP measurements and the WRF-Chem simulations. Over the Pacific Ocean, the prevailing westerly winds (at high altitudes) in northern hemisphere, on one hand, tend to keep the dust plume well above the underlying stratocumulus or stratus
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clouds over Pacific Ocean, making it being devoid of dry and wet deposition. In particular, the Aleutian cyclonic circulation over northern Pacific Ocean further carried dust plumes eastward to Alaska and western coastal region of Canada on 20 March 20, and 22 March, respectively. All of the abovementioned processes facilitate the long-range transport of dust plumes. As a first step in a series of efforts, integrated analyses based on multi-source observations and process-level model simulation have been applied in attempt to shed light on physical details in one individual SDS episode over time and space. This work has significant implications for long-range transport studies over other regions affected by dust or anthropogenic aerosols, although future observational and modeling work are warranted in order to assess the long-term climatological features regarding trans-Pacific transport of SDS, let alone the complicated interactions between dust aerosols and clouds during the transport processes. Acknowledgements This work was supported by the National Natural Science Foundation of China under Grants 41471301 and 91544217, the Ministry of Science and Technology under Grant 2017YFA0603501, Central Leading Local Development of Science and Technology Project in China under Grant HN 2016-149, the Climate Change Project of China Meteorological Administration (CMA) under Grant CCSF201732, and Chinese Academy of Meteorological Sciences under Grants 2017Z005, 2017Y002 and 2017R001. The PM2.5/PM10 and radiosonde data used in this paper were acquired from China Meteorological Administration, whereas the OMI/Aura and CALIOP/ CALIPSO data were obtained from NASA. The authors appreciate very much the NASA team for providing the reliable data used in this study. Last but not least, we are grateful to the editor and the four anonymous reviewers for their constructive comments, which help significantly improve the quality of this manuscript. Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.envpol.2017.07.062. References Alfaro-Contreras, R., Zhang, J., Campbell, J.R., Reid, J.S., 2016. Investigating the frequency and interannual variability in global above-cloud aerosol characteristics with CALIOP and OMI. Atmos. Chem. Phys. 16, 47e69. http://dx.doi.org/10.5194/ acp-16-47-2016. Amiridis, V., Wandinger, U., Marinou, E., Giannakaki, E., Tsekeri, A., Basart, S., Kazadzis, S., Gkikas, A., Taylor, M., Baldasano, J.M., Ansmann, A., 2013. Optimizing CALIPSO Saharan dust retrievals. Atmos. Chem. Phys. 13, 12089e12106. http://dx.doi.org/10.5194/acp-13-12089-2013, 14749-14795. Aoki, I., Kurosaki, Y., Osada, R., Sato, T., Kimura, F., 2005. Dust storms generated by mesoscale cold fronts in the Tarim Basin, Northwest China. Geophys. Res. Lett. 32 http://dx.doi.org/10.1029/2004GL021776. Chen, F., Dudhia, J., 2001. Coupling an advanced land surfaceehydrology model with the penn stateeNCAR MM5 modeling system. Part I: model implementation and sensitivity. Mon. Weather Rev. 129, 569e585. http://dx.doi.org/10.1175/ 1520-0493(2001)129<0587:CAALSH>2.0.CO;2. Chen, Z., Torres, O., McCormick, M.P., Smith, W., Ahn, C., 2002. Comparative study of aerosol and cloud detected by CALIPSO and OMI. Atmos. Environ. 51, 187e195. http://dx.doi.org/10.1016/j.atmosenv.2012.01.024. Chou, C.C.K., Chen, T.K., Huang, S.H., Liu, S.C., 2003. Radiative absorption capability of asian dust with black carbon contamination. Geophys. Res. Lett. 30 (12), 18e21. Clarke, A.D., Shinozuka, Y., Kapustin, V.N., Howell, S., Huebert, B., Doherty, S., Anderson, T., Covert, D., Anderson, J., Hua, X., Moore II, K.G., McNaughton, C., Carmichael, G., 2004. Size distributions and mixtures of dust and black carbon aerosol in asian outflow: physiochemistry and optical properties. J. Geophys. Res.- Atmos. 109 (15). D15S09 1e20. Creamean, J.M., Suski, K.J., Rosenfeld, D., Cazorla, A., DeMott, P.J., Sullivan, R.C., White, A.B., Ralph, F.M., Minnis, P., Comstock, J.M., Tomlinson, J.M., Prather, K.A., 2013. Dust and biological aerosols from the Sahara and Asia influence precipitation in the western U.S. Science 339, 1572e1578. http://dx.doi.org/10.1126/
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