Cloud scavenging of anthropogenic refractory particles at a mountain site in North China
Aerosol–cloud interactions remain a major source of uncertainty in climate forcing estimates. Few studies have been conducted to characterize the aerosol–cloud interactions in heavily polluted conditions worldwide. In this study, cloud residual and cloud interstitial particles were collected during cloud events under different pollution levels from 22 July to 1 August 2014 at Mt. Tai (1532 m above sea level) located in the North China Plain (NCP). A transmission electron microscope was used to investigate the morphology, size, and chemical composition of individual cloud residual and cloud interstitial particles, and to study mixing properties of different aerosol components in individual particles. Our results show that S-rich particles were predominant (78 %) during clean periods (PM2.5<15 µg m−3), but a large number of anthropogenic refractory particles (e.g., soot, fly ash, and metal) and their mixtures with S-rich particles (defined as “S-refractory”) were observed during polluted periods. Cloud droplets collected during polluted periods were found to become an extremely complicated mixture by scavenging abundant refractory particles. We found that 76 % of cloud residual particles were S-refractory particles and that 26 % of cloud residual particles contained two or more types of refractory particles. Soot-containing particles (i.e., S-soot and S-fly ash/metal-soot) were the most abundant (62 %) among cloud residual particles, followed by fly ash/metal-containing particles (i.e., S-fly ash/metal and S-fly ash/metal-soot, 37 %). These complicated cloud droplets have not been reported in clean continental or marine air before. Our findings provide an insight into the potential impacts on cloud radiative forcing from black carbon and metal catalyzed reactions of SO2 in micro-cloud droplets containing soluble metals released from fly ash and metals over polluted air.
Clouds play a crucial role in various physical and chemical processes occurring in the lower troposphere and hence affect the Earth's radiation budget (Seinfeld et al., 2016; Tilgner et al., 2014). Aerosol particles, including primary and secondary ones generated from natural and anthropogenic sources, either directly alter radiative forcing or act as cloud condensation nuclei (CCN) to indirectly influence it. At present, aerosol–cloud interactions unquestionably affect radiative forcing and global climate (McFiggans et al., 2006; Rosenfeld et al., 2014; Seinfeld and Pandis, 2006). CCN become cloud droplets through the condensation of water vapor when the relative humidity (RH) of an air parcel increases above saturation (Farmer et al., 2015). Size, chemical composition, and mixing state are main factors affecting the ability of a particle to act as CCN (Dusek et al., 2006; Fan et al., 2016; Hudson, 2007; Li et al., 2011a; Rosenfeld, 2000). In addition, aerosol particles incorporated into cloud droplets can be easily lifted into the free troposphere during cloud development and further extend their influence on cloud precipitation and regional climate (Fan et al., 2016).
Owing to rapid industrialization and urbanization in Asia, large quantities of aerosol particles from anthropogenic sources are released into the atmosphere, which can dramatically affect the chemical composition of CCN, and furthermore change the properties of clouds such as radiative forcing, lifetime, and precipitation patterns (Drewnick et al., 2007; Ervens, 2015; Li et al., 2011b; Twohy and Anderson, 2008). High concentrations of aerosol particles increase the number of cloud droplets and reduce their size, which further results in the reduction of precipitation efficiency and in extending the lifetime of clouds (Fan et al., 2016; J. Li et al., 2017; McFiggans et al., 2006; Qian et al., 2009; Rosenfeld, 2000). Moreover, anthropogenic aerosol particles – especially fly ash, metal, and soot particles – are incorporated into cloud droplets, and are transported long distances to affect ecosystems, human health, and radiative forcing (Li et al., 2013; Rosenfeld et al., 2014). In particular, the toxic and bioaccumulative metals can deposit into the ecosystem following fog or precipitation and further cause severe health problems to human beings (Liu et al., 2012). Moreover, transition metals such as iron (Fe) and manganese (Mn) can enhance the in-cloud oxidation of sulfur dioxide to sulfate (Harris et al., 2013).
Recently, many studies have been performed worldwide to investigate aerosol–cloud interactions and the composition of cloud droplets. Schroder et al. (2015) investigated the activation of refractory black carbon particles in stratocumulus clouds at a marine boundary layer site using a counterflow virtual impactor and single-particle soot photometer. Ueda et al. (2014) reported the effects of in-cloud processes on the compositional changes of sea salt particles by collecting individual aerosol particles in and below clouds, respectively. Pierce et al. (2015) calculated size distribution changes and radiative forcing effects due to the scavenging of interstitial particles by cloud droplets in a clean remote region. Roth et al. (2016) analyzed the composition and mixing state of cloud residues and out-of-cloud aerosol particles by single-particle aerosol mass spectrometry (SPAMS) on a mountain site and found that soot particles internally mixed with sulfate and nitrate were the dominant ones in cloud residues. All of the above studies were carried out in the clean atmosphere; they could not observe the clear interactions between abundant anthropogenic particles and cloud droplets. However, the latest satellite observations indicated that large numbers of anthropogenic fine particles assembled in the cloud base and might modify cloud properties in heavily polluted air influenced by industrial and urban emissions (Eck et al., 2018). Field observations are needed to confirm this and understand the interactions of aerosol–cloud over polluted areas, especially in North and South Asia.
Mt. Tai, the highest mountain in the NCP, is surrounded by several medium-sized industrial cities. The altitude of Mt. Tai is close to the top of the planetary boundary layer (PBL) above the NCP. Therefore, Mt. Tai is an ideal site to study the effects of regional transport and local emissions of anthropogenic aerosols on cloud properties. Numerous studies have been conducted on Mt. Tai, but virtually all the researchers mainly focus on the variation of chemical composition and size distribution of aerosol particles (Zhang et al., 2014) and the chemical composition of cloud water (J. Li et al., 2017; Wang et al., 2011). Because of the limitation of sampling and analyzing techniques, these studies did not consider the aerosol–cloud interactions at the top of Mt. Tai in North China.
Transmission electron microscopy (TEM) has become a powerful technique to characterize the particle morphology, size, and composition and mixing properties of different components in individual particles in recent years (Li et al., 2016a; Ueda et al., 2014). Many studies used SPAMS to characterize the composition of residual particles of individual cloud droplets (Lin et al., 2017; Pratt et al., 2010; Zhang et al., 2017). Compared to SPAMS, TEM can directly observe the morphology and different components of individual cloud droplet residual (cloud RES) and interstitial particles (cloud INT) (Kojima et al., 2004; Li et al., 2011a; Twohy and Anderson, 2008; Ueda et al., 2014). Therefore, the TEM technique can not only be used to identify cloud RES and cloud INT collected in a same cloud event but also reveal interactions between aerosol and clouds based on the different components within individual particles. In this study, we collected individual particles during cloud events at the summit of Mt. Tai and applied TEM to obtain and compare the morphology, size, and composition of cloud RES and cloud INT. This is helpful to understand the influence of anthropogenic sources on cloud properties above the heavily polluted region.
2.1 Sampling sites
Field observations were carried out at Mt. Tai (36.251∘ N, 117.101∘ E; 1532 m above sea level (a.s.l.)) from 22 July to 1 August 2014. Mt. Tai is the highest mountain in the central NCP and is surrounded by several medium-sized industrial cities (Fig. 1). A number of large coal-fired power plants, oil refinery plants, steel plants, and cement plants are located in these industrial cities (Jinan, Zibo, Laiwu, Liaocheng, Jining, Tai'an etc.) within a radius of 120 km around Mt. Tai (Fig. 1b). Jinan is the capital of Shandong Province and is situated 60 km north of Mt. Tai. Tai'an is located at the southern foot of Mt. Tai. Therefore, the local and regional emissions may have a large contribution to the air quality at the summit of Mt. Tai. Mt. Tai's altitude is close to the top of the PBL over the NCP, and local cloud events frequently occur at its summit, especially in summer.
As shown in Fig. 1c, individual particle samples were collected at a sampling site near the summit of Mt. Tai. The sampling site was usually covered by clouds when cloud events occurred during the sampling periods. The 24 h air mass backward trajectories arriving at Mt. Tai at 1500 m above ground level (a.g.l) (Fig. 1a) were calculated using the Hybrid Single-Particles Lagrangian Integrated Trajectory (HYSPLIT) model available at the NOAA Air Resources Laboratory's web server (Draxler and Rolph, 2003).
2.2 Individual particle collections
Individual aerosol particles were collected on carbon films supported by TEM copper grids (carbon type-B, 300-mesh copper, Beijing XXBR Technology Co., Ltd, China) using a single-stage cascade impactor with a 0.5 mm diameter jet nozzle at a flow rate of 1.0 L min−1. The aerodynamic diameter of particles collected with a 50 % efficiency (cutoff diameter, d50) by the sampler is 0.24 µm if particle density is 2 g cm−3. More detailed information about the setup of a modified sampler can be found in Li et al. (2011a). When cloud events occurred at the summit of Mt. Tai, individual particle samples were collected during the cloud events except one cloud event at midnight on 26 July (Fig. 3). The sample information in the present study is listed in Table 1.
During the sampling period, meteorological data at the summit of Mt. Tai including pressure (P), relative humidity (RH), temperature (T), wind speed (WS), and wind direction (WD) were measured and recorded every 5 min using a pocket weather meter (Kestrel 4500, Nielsen-Kellermann Inc., USA). PM2.5 concentrations on Mt. Tai were monitored online by a beta attenuation and optical analyzer (model 5030 SHARP monitor, Thermo Scientific, USA).
2.3 TEM analysis
Individual aerosol particles collected on TEM grids were analyzed using a transmission electron microscope (TEM, JEM-2100, JEOL Ltd., Japan) at a 200 kV accelerating voltage. TEM is equipped with an energy-dispersive X-ray spectrometer (EDS, INCA X-MaxN 80T, Oxford Instruments, UK). The EDS semi-quantitatively detects the elemental composition of individual particles with atomic number greater than 6 (Z>6). However, Cu peaks in the EDS spectra were not considered because of the interference from the copper substrate of TEM grids. We acquired morphology and composition of individual particles through the combination of TEM and EDS (TEM–EDS).
The distribution of aerosol particles on TEM grids was not uniform, with particle size decreasing from the center to the edge of the TEM grids. Cloud droplets with larger size normally impacted the center and interstitial particles mostly distributed on the peripheral areas of TEM grids (Li et al., 2011a). Moreover, cloud RES had large rims compared with cloud INT, suggesting that cloud RES were droplets before being captured (Zhang et al., 2006). According to the distribution and morphology of individual particles on the substrate, we can distinguish between cloud RES and cloud INT particles. Figure 2 generally displays typical TEM images of cloud RES and cloud INT particles. Generally, a number of previous studies using the cascade impactor have successfully captured individual interstitial particles and cloud droplets on the substrate during cloud events (Kojima et al., 2004; Li et al., 2011a; Ueda et al., 2014; Zhang et al., 2006).
To obtain the size of cloud RES and cloud INT particles, we measured the area and equivalent circle diameter (ECD) of these analyzed particles using iTEM software (Olympus soft imaging solutions GmbH, Germany). It should be noted that we measured ECD of the core of individual cloud RES excluding the water rim because the water rim only contains trace organics (Li et al., 2011a). The ECD can be further converted to equivalent spherical diameter according to the atomic force microscopy analysis (refer to the Supplement Fig. S1).
3.1 Meteorological conditions and backward trajectories
Temporal variations of pressure (P), relative humidity (RH), temperature (T), wind speed (WS), wind direction (WD), and PM2.5 concentration were measured on Mt. Tai from 22 July to 2 August 2014 (Fig. 3). During the sampling period, the temperature ranged from 12.6 to 29.4 ∘C, and the RH varied between 48.2 % and 100 %. Each day during the sampling period, the RH reached 100 % as temperatures decreased from the late afternoon into the evening (Fig. 3). We noticed that PM2.5 concentrations on the mountaintop were closely related to wind direction and speed during the regional transport of hazes. Based on backward trajectories of air masses and PM2.5 concentrations, the whole sampling period can be divided into three categories:
Clean period (PM2.5<15 µg m−3). The prevailing winds were from the northeast to east, and air masses were from higher altitudes above the marine areas, which led to the lowest PM2.5 concentration.
Lightly polluted period (15 µg m−3 < PM2.5 < 35 µg m−3). The prevailing winds were from the west, and air masses originating from higher altitudes above continental areas brought regional pollutants to the summit of Mt. Tai.
Polluted period (PM2.5 > 35 µg m−3). Air masses originating from the northwest, southwest, or south went through Tai'an.
Back trajectories as shown in Fig. 1a during polluted days suggest that air pollutants from industrialized cities might be lifted along the southern slope up to Mt. Tai's summit.
3.2 Mixing properties of anthropogenic refractory particles
Based on the elemental composition and morphology of individual particles, six basic types of individual particles were classified: S-rich (Fig. S2a), soot (Fig. S2b), organic matter (OM; Fig. S2c), mineral (Fig. S2d), and fly ash/metal (Fig. S2e–h). The classification criteria of different particle types and their sources have been described in a separate study (Li et al., 2016a). S-rich particles representing secondary inorganic particles (e.g., SO, NO, and NH) are transformed from gaseous SO2, NOx, and NH3. OM can be divided into primary organic matter (POM) and secondary organic matter (SOM). POM is directly emitted from coal or biomass burning and normally has spherical or irregular shapes (Liu et al., 2017), whereas SOM is produced from the chemical oxidation of volatile organic compounds (VOCs) and exhibits OM-coating on S-rich particles (Li et al., 2016b). Fly ash (e.g., Si, Al, and O) and metal particles (e.g., Fe, Mn, Zn, and Pb) normally are emitted from coal-fired power plants and heavy industrial activities, such as production activities in steel mills and smelters. Soot particles are generated from incomplete combustion processes of biomass burning and fossil fuels in both industrial activities and vehicular emissions. In much of the climate change and environmental literature, “soot” and “black carbon” are commonly used interchangeably, and black carbon is the most commonly used term in the climate science community (Andreae and Gelencsér, 2006; Buseck et al., 2014). In the following sections, we use the term soot for the classification of particle types and the term black carbon for the discussion of climate issues. Mineral particles come from construction activities, resuspended road dust, and natural soil. Among these types of particles, soot, POM, fly ash, mineral, and metal particles were refractory under electron beams and were thus defined as refractory particles (Ebert et al., 2016).
Based on mixing properties of multicomponents within individual particles (Figs. 4 and 5), these particles can be further classified into four categories: S-mineral (Figs. 4a and 5a), S-soot (Figs. 4b and 5b), S-fly ash/metal (Figs. 4c and 5c), and S-fly ash/metal-soot (Figs. 4d and 5d). Here, these four types of particles with refractory inclusions are generally defined as “S-refractory” particles.
Figure 6 shows number fractions of S-rich, refractory, and S-refractory particles in clean, lightly polluted, and polluted periods on Mt. Tai. In clean periods, S-rich particles had the highest proportion (78 %), followed by a 22 % contribution of the refractory and S-refractory particles. This may be attributed to the clean air masses that originated from the clean marine area and arrived at the summit of Mt. Tai through high-altitude transport (above 1500 m) (Fig. 1). Because the air masses did not contact the ground surface, the local anthropogenic pollutants (e.g., soot, fly ash, and metal) could not be lifted to the summit of Mt. Tai. Hence, secondary particles like S-rich particles were dominant in the clean period. In the lightly polluted and polluted periods, the fraction of S-rich particles decreased to 59 % and 44 %, respectively; meanwhile, the fractions of refractory and S-refractory increased up to 41 % and 56 %, respectively (Fig. 6). The backward trajectories suggest that these air masses went through the most heavily polluted areas before they arrived at the mountaintop (Fig. 1). Air masses on 2 polluted days (e.g., 22 and 31 July) were lifted from ground level to the atmospheric boundary layer. Our study shows that number fractions of refractory and S-refractory particles significantly increased from clean to polluted periods (Fig. 6). This result shows that large numbers of primary refractory particles from ground-level anthropogenic sources were lifted into the upper air and were further internally mixed with S-rich particles.
3.3 Comparisons of cloud RES and INT particles
During the sampling period, a fog monitor was used to measure the size of cloud droplets during cloud events (J. Li et al., 2017). This study reveals that in the cloud events, all the cloud droplets displayed particle size larger than 2 µm in which size range the interstitial particles were absent. Based on their different size, we can know that these cloud droplets and interstitial particles impacted different positions on the substrate. Although cloud droplets and interstitial particles dried after the collection, they can still be identified based on the distribution and morphology of individual particles in TEM images (Kojima et al., 2004; Li et al., 2011a; Ueda et al., 2014; Zhang et al., 2006). Cloud RES display larger size and large rims around their CCN (Figs. 2 and 4), which has not been observed in non-cloud events. In contrast, cloud INT impacted on the position away from the center of the sampling spot and their morphology looks like individual particles collected in non-cloud events. According to the rule, we can identify cloud RES and cloud INT in the samples collected during the cloud events.
Figure 7a shows that 100 % of cloud RES and 83 % of cloud INT contained S-rich species (i.e., S-rich and S-refractory). In other words, none of cloud RES were soot, fly ash/metal, and mineral particles, but 17 % of cloud INT were. Soot particles were mainly distributed in the finer size bins (<600 nm) of cloud INT (Fig. S3a). Interestingly, we found that 76 % of cloud RES were a mixture of sulfates and refractory particles, which is 3.5 times more than 22 % in cloud INT (Fig. 7a). Furthermore, 26 % of cloud RES had two or more types of inclusions (i.e., S-fly ash/metal-soot in Figs. 4d and 5d) but only 3 % of cloud INT did. Therefore, we can conclude that cloud RES are extremely complex mixtures formed when cloud droplets act like a collector to scavenge these refractory particles.
The size-resolved number fractions of different particle types in cloud RES and cloud INT indicate that S-rich particles were predominant from 60 nm to 1.2 µm in cloud INT (Fig. S3a), and S-refractory particles (indicated by the red box) dominated from 400 nm to 5.5 µm in cloud RES (Fig. S3b). Figure 7b shows that the median diameters of cloud RES and cloud INT were 1.19 µm and 422 nm, respectively. The size of cloud RES was much larger than that of cloud INT, suggesting that size is an important factor affecting the CCN ability (Dusek et al., 2006).
TEM observations in this study reveal that cloud RES contained large numbers of refractory-containing particles primarily emitted from various anthropogenic sources in the heavily polluted NCP. As much as 76 % of cloud RES were identified as S-refractory particles (Fig. 7a). We found that soot-containing particles (i.e., S-soot and S-fly ash/metal-soot) were the most abundant (62 %) among the cloud RES, followed by the relatively abundant fly ash/metal-containing particles (i.e., S-fly ash/metal and S-fly ash/metal-soot, 37 %) compared with 18 % and 7 % in the cloud INT, respectively (Fig. 7a). Although these refractory particles such as soot with hydrophobic properties could not be CCN directly, they can be easily accumulated by the existing cloud droplets as inclusions (Zuberi et al., 2005). In the heavily polluted NCP, large numbers of soot and fly ash/metal particles are released from anthropogenic sources (e.g., industrial activities and vehicular exhaust). During cloud events, abundant refractory particles can be efficiently entrained into existing liquid cloud droplets by wet scavenging. Li et al. (2011a) reported that particle number decreased dramatically during cloud formation at Mt. Tai with a scavenging ratio of 0.54, which demonstrated that aerosol particles could efficiently be incorporated into cloud droplets. Physical coagulation of interstitial particles with cloud droplets is an important process in developing clouds, which can lead to the reduction of cloud INT number and a size increase of cloud RES after the clouds dry (Pierce et al., 2015). As we know so far, the extremely complicated mixture of secondary and primary particles observed in the present study has seldom been found in cloud droplets in clean air over developed countries (Hao et al., 2013; Kojima et al., 2004; Schneider et al., 2017; Ueda et al., 2014), remote areas (Hiranuma et al., 2013) and the ocean (Hopkins et al., 2008; Twohy and Anderson, 2008; Zhang et al., 2006). For example, Zhang et al. (2006) reported that S-rich particles were predominant in the cloud RES with a small number fraction of sea salt particles over the Sea of Japan and soot or fly ash/metal particles were not observed. The present study reveals that individual cloud droplets are a far more complicated system in polluted air in North China than in the pristine continental and clean ocean air of the world.
Cloud properties such as albedo and lifetimes could be largely modified by the aerosol–cloud interactions, especially in heavily polluted regions (Wang et al., 2010, 2013). The model simulation revealed that black carbon aerosols had a noticeable impact (up to nearly 20 %) on cloud droplet number concentration in polluted black carbon source regions (Cherian et al., 2017). Especially, abundant black carbon particles incorporated into cloud droplets could lead to a decrease in cloud albedo by absorbing radiation and an increase of temperature in the troposphere, then an acceleration of the evaporation of the cloud droplets (Ackerman et al., 2000; Adachi et al., 2010; Wang et al., 2013; Zuberi et al., 2005). In the past few decades, precipitation was significantly reduced over east central China due to the large amount of anthropogenic aerosols (Qian et al., 2009; Zhao et al., 2006). Because an excess of aerosols in clouds could reduce precipitation, the nonprecipitating clouds in the NCP tend to evaporate back to aerosol particles by solar radiation. It is highly probable that abundant black carbon particles present in the cloud droplets in the heavily polluted NCP in this study (e.g., particles 1 and 2 in Fig. 8) significantly affected the cloud properties and regional climate.
Fly ash and metal particles are a typical “fingerprint” pointing to the coal-fired power plants and boilers in factories and heavy industries (e.g., steel plant and smelting factory) (Chen et al., 2012; Li et al., 2016a; Moffet et al., 2008). Indeed, the most intense emissions from various industries in the world occur in Hebei and Shandong provinces in the NCP (Qi et al., 2017). It is well known that these industrial activities continuously release anthropogenic pollutants via high stacks into the upper air. Liu et al. (2012) reported that the concentration of Zn reached 249.1 µg L−1 in the cloud and fog water samples at Mt. Tai, followed by Al (157.3 µg L−1), Fe (105.8 µg L−1), Pb (46.2 µg L−1), and Mn (42.8 µg L−1), which were much higher than those values reported at Mt. Schmücke in Germany (Fomba et al., 2015). Combining these results with our present study, we infer that fine primary particles emitted from these industrial activities might spread and be lifted to the upper air more easily than at ground level. These metal particles, especially Pb and Zn of nanometer size, can harm ecosystems and human health (Roberts et al., 2004). The fly ash and metal particles incorporated into cloud droplets (e.g., particle 1 in Fig. 8) could go through the atmospheric acid Fe dissolution processes during long-range transport reported by W. Li et al. (2017). If they were further transported to remote oceanic regions, soluble Fe species in the aerosol particles can fertilize plankton on the surface of the ocean (Ito and Shi, 2016; W. Li et al., 2017). Therefore, these anthropogenic fly ash/metal particles in polluted air contaminate cloud droplets and further amplify potential impacts of fine metal particles on the biogeochemical cycle in the troposphere.
Some studies suggested that the aqueous oxidation of SO2 to sulfate by H2O2 and O3 in cloud droplets was dominant at Mt. Tai (Shen et al., 2012). However, cloud water collected on Mt. Tai contained high concentrations of soluble Fe, Mn, Zn, and Pb (Liu et al., 2012). These soluble metals in cloud droplets are released from aqueous reactions between metal particles and acidic sulfates in cloud droplets (W. Li et al., 2017). Harris et al. (2013) estimated that the oxidation of SO2 in cloud droplets catalyzed by natural transition metal ions (TMIs) in mineral dust was dominant at Mt. Schmücke in Germany. For this study, how the soluble anthropogenic TMIs drive sulfate formation through TMI catalysis in micro-cloud droplets is still unresolved in polluted air. We propose that anthropogenic TMI catalysis contributing to sulfate production should be further studied in cloud droplets in the polluted NCP.
The nonprecipitating cloud processes over the polluted air of NCP quickly change the composition of aerosol particles and cloud droplets in the upper air, potentially causing various effects such as human health, regional climate, and biogeochemical cycle at the larger regional scale. To better illustrate the aerosol–cloud interactions in this study, we created the conceptual model of Fig. 9. The tall stacks of plants can emit smoke plumes that contain fine refractory particles and gaseous pollutants to the upper air. A portion of particles in urban areas can also be lifted to the mountaintop by prevailing valley winds. Once the clouds form on a mountaintop (or are later transported in other directions), these cloud droplets act as collectors to scavenge the refractory particles. These refractory particles as inclusions might complicate the cloud chemistry in micro-cloud droplets. Gaseous pollutants such as SO2, NOx, and VOCs may have enhanced aqueous oxidation potential in the complex cloud droplets. Our study is designed to better understand the aerosol–cloud interactions on the mountaintop in polluted industrial and urban areas. Recently, a study showed that the major aerosol pollution events with very high fine-mode aerosol optical depth (>1.0 in mid-visible) in the China–Korean Peninsula–Japan region are often observed to be associated with significant cloud cover (Eck et al., 2018). Therefore, we expect that large numbers of fine refractory particles from polluted areas scavenging in clouds have important impacts, not only at a local scale, but also at a large regional scale.
Individual aerosol particles were collected during cloud events on Mt. Tai from 22 July to 1 August 2014. Cloud RES and INT particles were separated by their distribution on TEM grids, and their composition was identified by TEM–EDS. Individual particles were classified into S-rich, refractory (i.e., mineral, soot, fly ash/metal), and S-refractory (i.e., S-mineral, S-soot, S-fly ash/metal, and S-fly ash/metal-soot). According to air mass backward trajectories and PM2.5 concentrations on Mt. Tai, the entire sampling period was divided into three classes: a clean period (PM2.5<15 µg m−3), a lightly polluted period (15 µg m−3 < PM2.5 < 35 µg m−3), and a polluted period (PM2.5 > 35 µg m−3). In the clean period, individual particles were dominated by S-rich particles (78 %), whereas the fraction of refractory particles and S-refractory particles increased significantly and dominated during the polluted periods. This suggested that anthropogenic pollutants from tall stacks of coal-fired power plants and heavy industries and vehicular exhaust in cities could be lifted to the summit of Mt. Tai under the prevailing southerly winds in summer.
TEM observations showed that 76 % of cloud RES were S-refractory particles contaminated by anthropogenic refractory particles, compared with only 22 % of cloud INT. Cloud RES displayed a larger size than cloud INT, which indicates that particle size decidedly affects CCN ability. Our study reveals that large numbers of anthropogenic refractory particles were incorporated into cloud droplets through in-cloud processes. It is especially important that abundant black carbon particles in cloud droplets could alter the radiative forcing of clouds and accelerate the evaporation of cloud droplets. The high concentrations of transition metal ions might favor the aqueous-phase oxidation of SO2 by O2 in cloud droplets under the heavily polluted conditions in the NCP. Fly ash/metal-containing cloud droplets could be transported long distances and harm ecosystems and human health through wet deposition. We propose a conceptual model to show the aerosol–cloud interactions on mountaintops influenced by heavily polluted air.
All data presented in this paper are available upon request. Please contact the corresponding author (email@example.com).
The supplement related to this article is available online at: https://doi.org/10.5194/acp-18-14681-2018-supplement.
LL and WL conceived the study and wrote the manuscript. LL and JZ collected the individual particle samples. LL, JZ, QY, and LX carried out the TEM and AFM measurements. All authors reviewed and commented on the paper.
The authors declare that they have no conflict of interest.
This article is part of the special issue “Regional transport and transformation of air pollution in eastern China”. It is not associated with a conference.
We appreciate Peter Hyde's comments and proofreading. We thank Liang Wen at
Shandong University for his assistance of sample collections. This work was
funded by the National Key R&D Program of China (2017YFC0212700), the National
Natural Science Foundation of China (41575116, 41622504, and 41805099), the State
Key Laboratory of Atmospheric Boundary Physics and Atmospheric Chemistry
(LAPC-KF-2017-02), and the Hundred Talents Program in Zhejiang
Edited by: Zhanqing Li
Reviewed by: two anonymous referees
Ackerman, A. S., Toon, O. B., Stevens, D. E., Heymsfield, A. J., Ramanathan, V., and Welton, E. J.: Reduction of tropical cloudiness by soot, Science, 288, 1042–1047, https://doi.org/10.1126/science.288.5468.1042, 2000.
Adachi, K., Chung, S. H., and Buseck, P. R.: Shapes of soot aerosol particles and implications for their effects on climate, J. Geophys. Res.-Atmos., 115, D15206, https://doi.org/10.1029/2009JD012868, 2010.
Andreae, M. O. and Gelencsér, A.: Black carbon or brown carbon? The nature of light-absorbing carbonaceous aerosols, Atmos. Chem. Phys., 6, 3131–3148, https://doi.org/10.5194/acp-6-3131-2006, 2006.
Buseck, P. R., Adachi, K., Gelencsér, A., Tompa, É., and Pósfai, M.: Ns-Soot: A Material-Based Term for Strongly Light-Absorbing Carbonaceous Particles, Aerosol Sci. Tech., 48, 777–788, https://doi.org/10.1080/02786826.2014.919374, 2014.
Chen, H., Laskin, A., Baltrusaitis, J., Gorski, C. A., Scherer, M. M., and Grassian, V. H.: Coal Fly Ash as a Source of Iron in Atmospheric Dust, Environ. Sci. Technol., 46, 2112–2120, https://doi.org/10.1021/es204102f, 2012.
Cherian, R., Quaas, J., Salzmann, M., and Tomassini, L.: Black carbon indirect radiative effects in a climate model, Tellus B, 69, 1369342, https://doi.org/10.1080/16000889.2017.1369342, 2017.
Draxler, R. R. and Rolph, G. D.: HYSPLIT (HYbrid Single-Particle Lagrangian Integrated Trajectory) Model access via NOAA ARL READY Website, http://ready.arl.noaa.gov/HYSPLIT.php (last access: 18 September 2018), NOAA Air Resources Laboratory, Silver Spring, MD, 2003.
Drewnick, F., Schneider, J., Hings, S. S., Hock, N., Noone, K., Targino, A., Weimer, S., and Borrmann, S.: Measurement of ambient, interstitial, and residual aerosol particles on a mountaintop site in central Sweden using an aerosol mass spectrometer and a CVI, J. Atmos. Chem., 56, 1–20, https://doi.org/10.1007/s10874-006-9036-8, 2007.
Dusek, U., Frank, G., Hildebrandt, L., Curtius, J., Schneider, J., Walter, S., Chand, D., Drewnick, F., Hings, S., and Jung, D.: Size matters more than chemistry for cloud-nucleating ability of aerosol particles, Science, 312, 1375–1378, https://doi.org/10.1126/science.1125261, 2006.
Ebert, M., Weigel, R., Kandler, K., Günther, G., Molleker, S., Grooß, J.-U., Vogel, B., Weinbruch, S., and Borrmann, S.: Chemical analysis of refractory stratospheric aerosol particles collected within the arctic vortex and inside polar stratospheric clouds, Atmos. Chem. Phys., 16, 8405–8421, https://doi.org/10.5194/acp-16-8405-2016, 2016.
Eck, T. F., Holben, B. N., Reid, J. S., Xian, P., Giles, D. M., Sinyuk, A., Smirnov, A., Schafer, J. S., Slutsker, I., Kim, J., Koo, J. H., Choi, M., Kim, K. C., Sano, I., Arola, A., Sayer, A. M., Levy, R. C., Munchak, L. A., O'Neill, N. T., Lyapustin, A., Hsu, N. C., Randles, C. A., Da Silva, A. M., Buchard, V., Govindaraju, R. C., Hyer, E., Crawford, J. H., Wang, P., and Xia, X.: Observations of the Interaction and Transport of Fine Mode Aerosols With Cloud and/or Fog in Northeast Asia from Aerosol Robotic Network (AERONET) and Satellite Remote Sensing, J. Geophys. Res.-Atmos., 123, 5560–5587, https://doi.org/10.1029/2018JD028313, 2018.
Ervens, B.: Modeling the Processing of Aerosol and Trace Gases in Clouds and Fogs, Chem. Rev., 115, 4157–4198, https://doi.org/10.1021/cr5005887, 2015.
Fan, J., Wang, Y., Rosenfeld, D., and Liu, X.: Review of Aerosol-Cloud Interactions: Mechanisms, Significance, and Challenges, J. Atmos. Sci., 73, 4221–4252, https://doi.org/10.1175/jas-d-16-0037.1, 2016.
Farmer, D. K., Cappa, C. D., and Kreidenweis, S. M.: Atmospheric Processes and Their Controlling Influence on Cloud Condensation Nuclei Activity, Chem. Rev., 115, 4199–4217, https://doi.org/10.1021/cr5006292, 2015.
Fomba, K. W., van Pinxteren, D., Müller, K., Iinuma, Y., Lee, T., Collett Jr., J. L., and Herrmann, H.: Trace metal characterization of aerosol particles and cloud water during HCCT 2010, Atmos. Chem. Phys., 15, 8751–8765, https://doi.org/10.5194/acp-15-8751-2015, 2015.
Hao, L., Romakkaniemi, S., Kortelainen, A., Jaatinen, A., Portin, H., Miettinen, P., Komppula, M., Leskinen, A., Virtanen, A., Smith, J. N., Sueper, D., Worsnop, D. R., Lehtinen, K. E. J., and Laaksonen, A.: Aerosol Chemical Composition in Cloud Events by High Resolution Time-of-Flight Aerosol Mass Spectrometry, Environ. Sci. Technol., 47, 2645–2653, https://doi.org/10.1021/es302889w, 2013.
Harris, E., Sinha, B., van Pinxteren, D., Tilgner, A., Fomba, K. W., Schneider, J., Roth, A., Gnauk, T., Fahlbusch, B., and Mertes, S.: Enhanced role of transition metal ion catalysis during in-cloud oxidation of SO2, Science, 340, 727–730, https://doi.org/10.1126/science.1230911, 2013.
Hiranuma, N., Brooks, S. D., Moffet, R. C., Glen, A., Laskin, A., Gilles, M. K., Liu, P., Macdonald, A. M., Strapp, J. W., and McFarquhar, G. M.: Chemical characterization of individual particles and residuals of cloud droplets and ice crystals collected on board research aircraft in the ISDAC 2008 study, J. Geophys. Res.-Atmos., 118, 6564–6579, https://doi.org/10.1002/jgrd.50484, 2013.
Hopkins, R. J., Desyaterik, Y., Tivanski, A. V., Zaveri, R. A., Berkowitz, C. M., Tyliszczak, T., Gilles, M. K., and Laskin, A.: Chemical speciation of sulfur in marine cloud droplets and particles: Analysis of individual particles from the marine boundary layer over the California current, J. Geophys. Res.-Atmos., 113, D04209, https://doi.org/10.1029/2007jd008954, 2008.
Hudson, J. G.: Variability of the relationship between particle size and cloud-nucleating ability, Geophys. Res. Lett., 34, L08801, https://doi.org/10.1029/2006gl028850, 2007.
Ito, A. and Shi, Z.: Delivery of anthropogenic bioavailable iron from mineral dust and combustion aerosols to the ocean, Atmos. Chem. Phys., 16, 85–99, https://doi.org/10.5194/acp-16-85-2016, 2016.
Kojima, T., Buseck, P. R., Wilson, J. C., Reeves, J. M., and Mahoney, M. J.: Aerosol particles from tropical convective systems: Cloud tops and cirrus anvils, J. Geophys. Res.-Atmos., 109, D12201, https://doi.org/10.1029/2003JD004504, 2004.
Li, J., Wang, X., Chen, J., Zhu, C., Li, W., Li, C., Liu, L., Xu, C., Wen, L., Xue, L., Wang, W., Ding, A., and Herrmann, H.: Chemical composition and droplet size distribution of cloud at the summit of Mount Tai, China, Atmos. Chem. Phys., 17, 9885–9896, https://doi.org/10.5194/acp-17-9885-2017, 2017.
Li, W., Li, P., Sun, G., Zhou, S., Yuan, Q., and Wang, W.: Cloud residues and interstitial aerosols from non-precipitating clouds over an industrial and urban area in northern China, Atmos. Environ., 45, 2488–2495, https://doi.org/10.1016/j.atmosenv.2011.02.044, 2011a.
Li, W. J., Zhang, D. Z., Shao, L. Y., Zhou, S. Z., and Wang, W. X.: Individual particle analysis of aerosols collected under haze and non-haze conditions at a high-elevation mountain site in the North China plain, Atmos. Chem. Phys., 11, 11733–11744, https://doi.org/10.5194/acp-11-11733-2011, 2011b.
Li, W., Wang, Y., Collett, J. L., Chen, J., Zhang, X., Wang, Z., and Wang, W.: Microscopic Evaluation of Trace Metals in Cloud Droplets in an Acid Precipitation Region, Environ. Sci. Technol., 47, 4172–4180, https://doi.org/10.1021/es304779t, 2013.
Li, W., Shao, L., Zhang, D., Ro, C.-U., Hu, M., Bi, X., Geng, H., Matsuki, A., Niu, H., and Chen, J.: A review of single aerosol particle studies in the atmosphere of East Asia: morphology, mixing state, source, and heterogeneous reactions, J. Clean Prod., 112, 1330–1349, https://doi.org/10.1016/j.jclepro.2015.04.050, 2016a.
Li, W., Sun, J., Xu, L., Shi, Z., Riemer, N., Sun, Y., Fu, P., Zhang, J., Lin, Y., and Wang, X.: A conceptual framework for mixing structures in individual aerosol particles, J. Geophys. Res.-Atmos., 121, 13784–13798, https://doi.org/10.1002/2016JD025252, 2016b.
Li, W., Xu, L., Liu, X., Zhang, J., Lin, Y., Yao, X., Gao, H., Zhang, D., Chen, J., and Wang, W.: Air pollution–aerosol interactions produce more bioavailable iron for ocean ecosystems, Sci. Adv., 3, e1601749, https://doi.org/10.1126/sciadv.1601749, 2017.
Lin, Q., Zhang, G., Peng, L., Bi, X., Wang, X., Brechtel, F. J., Li, M., Chen, D., Peng, P., Sheng, G., and Zhou, Z.: In situ chemical composition measurement of individual cloud residue particles at a mountain site, southern China, Atmos. Chem. Phys., 17, 8473–8488, https://doi.org/10.5194/acp-17-8473-2017, 2017.
Liu, L., Kong, S., Zhang, Y., Wang, Y., Xu, L., Yan, Q., Lingaswamy, A. P., Shi, Z., Lv, S., Niu, H., Shao, L., Hu, M., Zhang, D., Chen, J., Zhang, X., and Li, W.: Morphology, composition, and mixing state of primary particles from combustion sources – crop residue, wood, and solid waste, Sci. Rep., 7, 5047, https://doi.org/10.1038/s41598-017-05357-2, 2017.
Liu, X., Wai, K. M., Wang, Y., Zhou, J., Li, P., Guo, J., Xu, P., and Wang, W.: Evaluation of trace elements contamination in cloud/fog water at an elevated mountain site in Northern China, Chemosphere, 88, 531–541, https://doi.org/10.1016/j.chemosphere.2012.02.015, 2012.
McFiggans, G., Artaxo, P., Baltensperger, U., Coe, H., Facchini, M. C., Feingold, G., Fuzzi, S., Gysel, M., Laaksonen, A., Lohmann, U., Mentel, T. F., Murphy, D. M., O'Dowd, C. D., Snider, J. R., and Weingartner, E.: The effect of physical and chemical aerosol properties on warm cloud droplet activation, Atmos. Chem. Phys., 6, 2593–2649, https://doi.org/10.5194/acp-6-2593-2006, 2006.
Moffet, R. C., Desyaterik, Y., Hopkins, R. J., Tivanski, A. V., Gilles, M. K., Wang, Y., Shutthanandan, V., Molina, L. T., Abraham, R. G., Johnson, K. S., Mugica, V., Molina, M. J., Laskin, A., and Prather, K. A.: Characterization of Aerosols Containing Zn, Pb, and Cl from an Industrial Region of Mexico City, Environ. Sci. Technol., 42, 7091–7097, https://doi.org/10.1021/es7030483, 2008.
Pierce, J. R., Croft, B., Kodros, J. K., D'Andrea, S. D., and Martin, R. V.: The importance of interstitial particle scavenging by cloud droplets in shaping the remote aerosol size distribution and global aerosol-climate effects, Atmos. Chem. Phys., 15, 6147–6158, https://doi.org/10.5194/acp-15-6147-2015, 2015.
Pratt, K. A., Twohy, C. H., Murphy, S. M., Moffet, R. C., Heymsfield, A. J., Gaston, C. J., DeMott, P. J., Field, P. R., Henn, T. R., Rogers, D. C., Gilles, M. K., Seinfeld, J. H., and Prather, K. A.: Observation of playa salts as nuclei in orographic wave clouds, J. Geophys. Res.-Atmos., 115, D15301, https://doi.org/10.1029/2009jd013606, 2010.
Qi, J., Zheng, B., Li, M., Yu, F., Chen, C., Liu, F., Zhou, X., Yuan, J., Zhang, Q., and He, K.: A high-resolution air pollutants emission inventory in 2013 for the Beijing-Tianjin-Hebei region, China, Atmos. Environ., 170, 156–168, https://doi.org/10.1016/j.atmosenv.2017.09.039, 2017.
Qian, Y., Gong, D., Fan, J., Leung, L. R., Bennartz, R., Chen, D., and Wang, W.: Heavy pollution suppresses light rain in China: Observations and modeling, J. Geophys. Res.-Atmos., 114, D00K02, https://doi.org/10.1029/2008JD011575, 2009.
Roberts, J. R., Taylor, M. D., Castranova, V., Clarke, R. W., and Antonini, J. M.: Soluble metals associated with residual oil fly ash increase morbidity and lung injury after bacterial infection in rats, J. Toxicol. Env. Health Part A, 67, 251–263, https://doi.org/10.1080/15287390490266927, 2004.
Rosenfeld, D.: Suppression of rain and snow by urban and industrial air pollution, Science, 287, 1793–1796, https://doi.org/10.1126/science.287.5459.1793, 2000.
Rosenfeld, D., Sherwood, S., Wood, R., and Donner, L.: Climate effects of aerosol-cloud interactions, Science, 343, 379–380, https://doi.org/10.1126/science.1247490, 2014.
Roth, A., Schneider, J., Klimach, T., Mertes, S., van Pinxteren, D., Herrmann, H., and Borrmann, S.: Aerosol properties, source identification, and cloud processing in orographic clouds measured by single particle mass spectrometry on a central European mountain site during HCCT-2010, Atmos. Chem. Phys., 16, 505–524, https://doi.org/10.5194/acp-16-505-2016, 2016.
Schneider, J., Mertes, S., van Pinxteren, D., Herrmann, H., and Borrmann, S.: Uptake of nitric acid, ammonia, and organics in orographic clouds: mass spectrometric analyses of droplet residual and interstitial aerosol particles, Atmos. Chem. Phys., 17, 1571–1593, https://doi.org/10.5194/acp-17-1571-2017, 2017.
Schroder, J. C., Hanna, S. J., Modini, R. L., Corrigan, A. L., Kreidenwies, S. M., Macdonald, A. M., Noone, K. J., Russell, L. M., Leaitch, W. R., and Bertram, A. K.: Size-resolved observations of refractory black carbon particles in cloud droplets at a marine boundary layer site, Atmos. Chem. Phys., 15, 1367–1383, https://doi.org/10.5194/acp-15-1367-2015, 2015.
Seinfeld, J. H. and Pandis, S. N.: Atmospheric chemistry and physics: from air pollution to climate change, John Wiley & Sons, 2006.
Seinfeld, J. H., Bretherton, C., Carslaw, K. S., Coe, H., DeMott, P. J., Dunlea, E. J., Feingold, G., Ghan, S., Guenther, A. B., Kahn, R., Kraucunas, I., Kreidenweis, S. M., Molina, M. J., Nenes, A., Penner, J. E., Prather, K. A., Ramanathan, V., Ramaswamy, V., Rasch, P. J., Ravishankara, A. R., Rosenfeld, D., Stephens, G., and Wood, R.: Improving our fundamental understanding of the role of aerosol-cloud interactions in the climate system, P. Natl. Acad. Sci. USA, 113, 5781–5790, https://doi.org/10.1073/pnas.1514043113, 2016.
Shen, X. H., Lee, T., Guo, J., Wang, X., Li, P., Xu, P., Wang, Y., Ren, Y., Wang, W., Wang, T., Li, Y., Cam, S. A., and Collett, J. L.: Aqueous phase sulfate production in clouds in eastern China, Atmos. Environ., 62, 502–511, https://doi.org/10.1016/j.atmosenv.2012.07.079, 2012.
Tilgner, A., Schöne, L., Bräuer, P., Van Pinxteren, D., Hoffmann, E., Spindler, G., Styler, S., Mertes, S., Birmili, W., and Otto, R.: Comprehensive assessment of meteorological conditions and airflow connectivity during HCCT-2010, Atmos. Chem. Phys., 14, 9105–9128, https://doi.org/10.5194/acp-14-9105-2014, 2014.
Twohy, C. H. and Anderson, J. R.: Droplet nuclei in non-precipitating clouds: composition and size matter, Environ. Res. Lett., 3, 045002, https://doi.org/10.1088/1748-9326/3/4/045002, 2008.
Ueda, S., Hirose, Y., Miura, K., and Okochi, H.: Individual aerosol particles in and below clouds along a Mt. Fuji slope: Modification of sea-salt-containing particles by in-cloud processing, Atmos. Res., 137, 216–227, https://doi.org/10.1016/j.atmosres.2013.10.011, 2014.
Wang, J., Cubison, M. J., Aiken, A. C., Jimenez, J. L., and Collins, D. R.: The importance of aerosol mixing state and size-resolved composition on CCN concentration and the variation of the importance with atmospheric aging of aerosols, Atmos. Chem. Phys., 10, 7267–7283, https://doi.org/10.5194/acp-10-7267-2010, 2010.
Wang, Y., Guo, J., Wang, T., Ding, A., Gao, J., Zhou, Y., Collett, J. L., and Wang, W.: Influence of regional pollution and sandstorms on the chemical composition of cloud/fog at the summit of Mt. Taishan in northern China, Atmos. Res., 99, 434–442, https://doi.org/10.1016/j.atmosres.2010.11.010, 2011.
Wang, Z., Zhang, H., Li, J., Jing, X., and Lu, P.: Radiative forcing and climate response due to the presence of black carbon in cloud droplets, J. Geophys. Res.-Atmos., 118, 3662–3675, https://doi.org/10.1002/jgrd.50312, 2013.
Zhang, D., Ishizaka, Y., and Aryal, D.: Individual particles and droplets in continentally influenced stratocumulus: A case study over the Sea of Japan, Atmos. Res., 79, 30–51, https://doi.org/10.1016/j.atmosres.2005.04.003, 2006.
Zhang, G., Lin, Q., Peng, L., Bi, X., Chen, D., Li, M., Li, L., Brechtel, F. J., Chen, J., Yan, W., Wang, X., Peng, P., Sheng, G., and Zhou, Z.: The single-particle mixing state and cloud scavenging of black carbon: a case study at a high-altitude mountain site in southern China, Atmos. Chem. Phys., 17, 14975–14985, https://doi.org/10.5194/acp-17-14975-2017, 2017.
Zhang, Y. M., Zhang, X. Y., Sun, J. Y., Hu, G. Y., Shen, X. J., Wang, Y. Q., Wang, T. T., Wang, D. Z., and Zhao, Y.: Chemical composition and mass size distribution of PM1 at an elevated site in central east China, Atmos. Chem. Phys., 14, 12237–12249, https://doi.org/10.5194/acp-14-12237-2014, 2014.
Zhao, C., Tie, X., and Lin, Y.: A possible positive feedback of reduction of precipitation and increase in aerosols over eastern central China, Geophys. Res. Lett., 33, L11814, https://doi.org/10.1029/2006gl025959, 2006.
Zuberi, B., Johnson, K. S., Aleks, G. K., Molina, L. T., and Laskin, A.: Hydrophilic properties of aged soot, Geophys. Res. Lett., 32, L01807, https://doi.org/10.1029/2004gl021496, 2005.