the inﬂuences of macro- and microphysical characteristics

ADVANCES IN ATMOSPHERIC SCIENCES, VOL. 31, MAY 2014, 624–636

The Influences of Macro- and Microphysical Characteristicsof Sea-Fog

on Fog-Water Chemical Composition

YUE Yanyu1,2, NIU Shengjie∗1, ZHAO Lijuan1, ZHANG Yu3, and XU Feng4

1Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,

Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration,

Nanjing University of Information Science & Technology, Nanjing 2100442Wuhan Central Meteorological Observatory, Wuhan 430074

3Zhanjiang Meteorological Bureau, Zhanjiang 5240014Guangdong Ocean University, Zhanjiang 524009

(Received 25 March 2013; revised 9 August 2013; accepted 25 September 2013)

ABSTRACT

During a sea-fog field observation campaign on Donghai Island in the spring of 2011, fog-water, visibility, meteorologicalelements, and fog droplet spectra were measured. The main cations and anions in 191 fog-water samples were Na+, NH+

4 ,H+, NO−

3 , Cl− and SO2−4 , and the average concentrations of cations and anions were 2630 and 2970µeq L−1, respectively.

The concentrations of Na+ and Cl− originated from the ocean were high. The enhancement of anthropogenic pollution mighthave contributed to the high concentration of NH+

4 , H+, and NO−3 . The average values of pH and electrical conductivity (EC)were 3.34 and 505µS cm−1, respectively, with a negative correlation between them. Cold fronts associated with cycloniccirculations promoted the decline of ion loadings. Air masses from coastal areas had the highest ion loadings, contrarytothose from the sea. The ranges of wind speed, wind direction and temperature corresponding to the maximum total ionconcentration (TIC) were 3.5–4 m s−1, 79◦–90◦ and 21◦C–22◦C, respectively. In view of the low correlation coefficients, anew parameter Lr was proposed as a predictive parameter for TIC and the correlation coefficient increased to 0.74. Based onaerosol concentrations during the sea-fog cases in 2010, weconfirmed that fog-water chemical composition also dependedon the species and sizes of aerosol particles. When a dust storm passed through Donghai Island, the number concentrationof large aerosol particles (with diameter> 1 µm) increased. This caused the ratio of Ca2+/Na+ in fog-water to increasesignificantly.

Key words: ion concentration, synoptic weather system, meteorological element, fog microphysics, aerosol

Citation : Yue, Y. Y., S. J. Niu, L. J. Zhao, Y. Zhang, and F. Xu, 2014: Theinfluences of macro- and microphysical character-istics of sea fog on fog-water chemical composition.Adv. Atmos. Sci., 31(3), 624–636, doi: 10.1007/s00376-013-3059-2.

1. Introduction

Fog has an important influence on the environment, eco-logical cycle and human lives, and so the properties of fog-water have long been studied by the global scientific commu-nity (Fuzzi et al., 1984; Fan et al., 2010; Strater et al., 2010).On the one hand, while fog deposition in forest regions isimportant for both vegetation growth and water balance, andfog-water collection systems have been used to solve watershortages in South Africa (Wrzesinsky and Klemm, 2000;Jaen, 2002); on the other hand, enriched organic substancesand droplets of 2–8µm on foggy days can be damaging to hu-man health if inhaled (Millet et al., 1996; Fan et al., 2009a).

Research on fog-water ion concentration has received a

∗ Corresponding author: NIU ShengjieEmail: [email protected]

great deal of attention, and one of the major findings is thatthe influence of marine conditions is usually either weak ornegligible for continental fogs (Lu et al., 2010). The maininorganic ions, including SO2−4 , NO−

3 , Cl−, NH+4 , Ca2+, and

Mg2+, are produced by anthropogenic contamination, suchas industrial production, automobile emissions, buildingcon-struction, and so on (Millet et al., 1996; Ali et al., 2004; Błaset al., 2010). The dominant ions of sea fog are Na+ andCl−, implying the contribution of oceanic aerosols (Mo etal., 1989; Ali et al., 2004). However, pollutants generatedonland could also affect the fog-water chemical composition incoastal areas. Sometimes, the acidification of sea-fog mightbe influenced by the stable end-products of dimethyl sulfide(DMS) oxidation in the atmosphere (Deininger and Saxena,1997; Sasakawa and Uematsu, 2005; Raja et al., 2008).

Ion concentrations of fog-water can be affected by manyfactors, such as synoptic systems, properties of the boundary

© Institute of Atmospheric Physics/Chinese Academy of Sciences, and Science Press and Springer-Verlag Berlin Heidelberg 2014

MAY 2014 YUE ET AL. 625

layer and air masses, meteorological elements, and the mi-crophysical characteristics of fog (Wrzesinsky and Klemm,2000; Igawa et al., 2001; Collett et al., 2002; Koracin et al.,2005; Błas et al., 2010). Most previous studies have focusedon the influence of the air masses transportation on the sourceof pollutants (Fisak et al., 2004; Strater et al., 2010; Li et al.,2011), since different wind directions could bring differentpollutants from different regions. The results of the stud-ies on synoptic system considered to be the main influenceon the vertical diffusion of pollutants have shown us that theaverage total ion concentration (TIC) under an anticycloniccirculation is generally higher than that under a cyclonic cir-culation or a transition system (Collett et al., 2002; Błasetal., 2010).

The microphysical structure of fog has also been foundto vary systematically according to air parcel trajectory andair mass history (Goodman, 1977). However, long-term sam-pling is important for analyzing the effects of microphysi-cal dynamics on the chemical composition of cloud or fog(Moller et al., 1996). Some research has shown relation-ships between microphysical quantities and fog-water chem-istry (Arends et al., 1994; Fuzzi et al., 1996; Moller et al.,1996; Elbert et al., 2000). For example, high levels of humid-ity carried by westerly winds can lead to rainfall and higherliquid water content (LWC), which favors lower ion concen-trations (Wrzesinsky and Klemm, 2000). Furthermore, ionconcentrations of fog-water formed on mountain slopes wasshown to depend on air pollutant concentrations and proper-ties of the fog (Igawa et al., 1998). Aikawa et al. (2007) andYang et al. (2010) pointed out that both the concentrations ofgases/aerosols and scavenging processes have impacts on ionconcentrations in fog episodes. Due to the curvature effect,coarse particles are more likely to serve as fog condensationnuclei (FCN) and can be cleared away by sea-fog effectively(Sasakawa et al., 2003; Fahey et al., 2005). After fog forma-tion, the aerosol particles and gases could enter fog dropletsby Brownian motion or diffusion to participate in chemicalreactions.

Fog-water chemistry analysis in China did not start un-til the 1980s; but recently, numerous fog-water observationcampaigns have been carried out in different areas (Niu etal., 2010a). Fog-water ion concentrations are higher in ur-ban areas (Bao et al., 1995; Fan et al., 2009b) than coastalareas (Yang et al., 1989; Song et al., 1992), and differencesamong observation sites reflect the influence on fog-water ofdifferent pollutant sources. Na+ and Cl− are the main ionspresent in fogs over the East China Sea (Mo et al., 1989; Xuet al., 2011a), while SO2−4 and Ca2+ are more prevalent infogs over large cities (Li et al., 2011). Sea-fog observationsalong South China’s coastal areas are more limited. Finally,some studies pointed out that air masses from different di-rections give different ion concentrations, and revealed somesimple relationships between ion concentrations and micro-physical quantities (Li et al., 2008; Lu et al., 2010).

It is essential to study sea-fog due to its influence ontraffic, fishing and naval activity. Recent fog studies on theLeizhou Peninsular focused on microphysics, boundary layer

dynamics, and ion concentrations of sea-fog water (Yue et al.,2012, 2013; Zhang et al., 2013). However, systematic studieson the factors that influence fog-water are lacking. It is alsodifficult to obtain accurate relationships between TIC and mi-crophysical quantities based on statistical analysis, owing tolimited fog-water samples. To gain a better understanding ofthe primary factors that influence the evolution of ion com-position, observations were conducted in the springs of 2010and 2011 on Donghai Island. The study had two objectives:to obtain the basic characteristics of the chemical composi-tion of sea-fog water in this region; and to investigate thecharacteristics of macro- and microphysical factors influenc-ing the chemical composition of the sea-fog, including syn-optic systems, air-mass trajectories, fog microphysical char-acteristics, and aerosol spectra.

2. Experiments, instruments and analysesThe observation site in 2011 was the radar station on

Donghai Island (21◦0′50′′N, 110◦31′19′′E; 50 m above sealevel) in Zhanjiang, Guangdong Province, about 800 m awayfrom the shoreline. The basic details of the first observationin 2010, along with the calculation methods used on the data,can be found in Yue et al. (2012). The second field observa-tion was carried out from 19 February to 23 March 2011.

Donghai Island is located in the eastern part of LeizhouPeninsula, which itself is located north of the South ChinaSea. Seasonally, the frequency of sea-fog is highest in spring,with the average number of foggy days in Zhanjiang being24.7 d yr−1 (Xu et al., 2011b). Because the Wide-Range Par-ticle Spectrometer used to measure aerosols was not installedin the 2011 observation, the data collected in 2010 were usedto study the influence of aerosols.

The observational instruments included a fog-water col-lector, a visibility meter (VPF730), a fog droplet spectrom-eter (FM-100 Droplet Measurement System), and an auto-matic meteorological station (WP3103). Details regardingthese four instruments can be found in Demoz et al. (1996),Niu et al. (2010b), Yue et al. (2012), and Zhao et al. (2013).

The Wide-Range Particle Spectrometer measuresaerosols by combining a Laser Particle Spectrometer (LPS),Differential Mobility Analysis (DMA), and CondensationParticle Counting (CPC). It can measure concentrations andsize distributions of aerosols from 5 to 10 000 nm in diame-ter. A sample of 0.7 L min−1 passes through the LPS of 350nm to 10µm in diameter, and the remaining 0.3 L min−1

passes through the DMA of 10–500 nm in diameter; they arethen counted by the CPC. The temporal resolution of the datais 5 min.

The pH and electrical conductivity (EC) were measuredby a pH meter (PHS-25/PHS-29) and a conductivity me-ter (DDSJ-308A), respectively. The fog-water ion concen-trations were detected by ion chromatography (IntelligentIon Chromatography-Professional IC 850, Metrohm Ltd,Switzerland), in which the anions and cations can be analyzedautomatically and synchronously. The system setup for anionanalysis included a separation column (Metrosep A Supp 7-

626 INFLUENCES OF DIFFERENT FACTORS ON FOG-WATER CHEMICAL COMPOSITION VOLUME 31

250), a guard column (Metrosep A Supp 4/5), a conductivitydetector, and a weak base elunet (3.6 mmol L−1 Na2CO3)with a flow rate of 0.7 mL min−1. The setup for cation analy-sis included a separation column (Metrosep C 4-150), a guardcolumn (Metrosep C4 GUARD), a conductivity detector, anda weak acid elunet (1.7 mmol L−1 HNO3 and 0.7 mmol L−1

pyridinedicarboxylic acid) with a flow rate of 0.9 mL min−1.Before the analysis, the fog-water samples were first filteredthrough a cellulose acetate membrane (0.45µm) and then putinto an automatic injector. The concentration of suppressorregeneration fluid (H2SO4) was greater than 50 mmol L−1.In terms of quality control of the data, if the ion concentra-tion of fog-water was very high, the samples were diluted fivetimes and reanalyzed to prevent the ion’s curve from deviat-ing significantly from that of the standard solution.

Backward trajectory analysis was based on the trajec-tory clusters of the HYSPLET4 (Hybrid Single-Particle La-grangian Integrated Trajectory) model. Detailed informationon the model can be found in Draxler and Hess (1998).

3. Results and discussion

3.1. Chemical characteristics of fog water

The basic results from the 13 fog-water collection casesare shown in Table 1 and Fig. 1. The total number of fog-water samples from the 13 cases was 191. The values of ECranged from 57 to 3270µS cm−1, with an average value of505µS cm−1. The values of pH ranged from 2.28 to 4.96,concentrating between 3.10 and 3.70 (Fig. 2), and the aver-age value was 3.34. There was a significant, negative corre-lation between pH and EC, with the least-squares best fit anda correlation coefficient of−0.87.

y = 1.39exp(−x/415)+2.71 , (1)

wherey is pH of the samples, andx is electrical conductivity(in units ofµS cm−1). The main cations and anions includedNa+, NH+

4 , H+, NO−

3 , Cl−, and SO2−4 , with average con-

centrations of 791, 714, 670, 1159, 922, and 883µeq L−1,respectively (Fig. 1). The average cation and anion concen-trations for the 13 cases were 2630 and 2970µeq L−1, re-spectively, with an average ratio of 0.94. The percentage dif-ference of the ion balance (P) can be calculated, as follows:

P = (Canions−Ccations)/(Canions+Ccations)×100%, (2)

whereCanions andCcations are the ion concentrations of an-ions and cations, respectively. The average value ofP was3%, with a standard deviation of 3.8. The values ofP rangedfrom −14% to 21%, with most values lying in the range of−25.8%–10.4% (Fuzzi et al., 1992; Błas et al., 2010).

The range of pH values found in this study is almostthe same as that for the eastern South Pacific Ocean re-ported by Strater et al. (2010), which was 2.90–3.50, and inStrasbourg, France, reported by Millet et al. (1996), whichwas 2.79–5.70. Besides, the lowest pH value of fog-waterreported over Los Angeles and San Francisco was 2.20 Ta

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1 01 0 01 0 0 0C a t i o n s a n d a n i o n sTIC( �eqL�1 )

N a + H + N H 4 + K + C a 2 + M g 2 + C l N O 3 S O 4 2 Fig. 1. Average concentrations of different cations and an-ions.The large boxes represent the interquartile range from the25th to the 75th percentile. The small boxes and the line insideeach large box indicate the mean and median values, respec-tively. The “whiskers” extend upward to the 95th percentileanddownward to the 5th percentile.

2 . 4 2 . 7 3 . 0 3 . 3 3 . 6 3 . 9 4 . 2 4 . 5 4 . 8 5 . 101 02 03 04 05 06 0N umb eroff og wat ersampl es

p HFig. 2. Number of fog-water samples in different pH ranges.

(Munger et al., 1983). The acidity of fog-water in southernFujian Province was reported as high, while ion concentra-tions were lower, since pH is calculated by the concentra-tion of H+ after the neutralization reaction (Liu et al., 1996).Johnson et al. (1987) found that high concentrations of HNO3

and H2SO4 affected the pH of fog-water over California. Wealso found NH+4 , NO−

3 , and SO2−4 played more improtant

roles in determining the pH over Donghai Island. The cor-relation coefficients between H+ and NH+

4 , NO−

3 , or SO2−4

ranged between 0.7–0.8 (Table 2). Fractional acidity (FA,FA = [H+]/[nssSO2−

4 ] + [NO−

3 ]) was proposed by Daum etal. (1984). By assuming that all H+ originates from HNO3and H2SO4, FA is equal to 1 when there is no neutralizationreaction. The proportion of FA values greater than 0.3 was82%, suggesting there was a large amount of H+ originatedfrom HNO3 and H2SO4 not taking part in the neutralizationreaction that led to low pH.

To further study ion characteristics, ion correlations andratios were obtained (Tables 2 and 3). As can be seen inthe data, the correlation coefficient between Na+ and Cl−

was high, reaching 0.97, while the correlation coefficientsbe-

tween Na+ and NO−3 or SO2−4 were in the range of 0.8–0.9.

In inland regions, the correlation between Na+ and Cl− isweak (Lu et al., 2010). The concentrations of Na+ and Cl−

were larger than those of the other ions, which mainly oc-curred in those samples with a long collection time (Table 1),such as cases 3, 4, 5, 6, and 7. When the collection time of asample was long, the non-ocean aerosols from anthropogenicemissions from the island and distant industrial regions wereeasily cleared away by gravitational settling during the long-distance transport. Meanwhile, the concentration of Cl− washigher than that of Na+, with the average ratio being 1.46 onDonghai Island. Keene et al. (1986) pointed out that the ratioof Cl− and Na+ is typically about 1.17, indicating that theremay be other possible anthropogenic sources. The correlationanalysis reveals that the correlation coefficients betweenCl−

and Na+, Mg2+, or Ca2+ were all above 0.9, suggesting thatCl− was not only introduced in the form of NaCl, but otherchlorides as well. However, during long-distance transportof sea-salt particles, Cl− tends to be lost through sedimenta-tion and the escape of HCl, which explains the result that theconcentration of Na+ is often larger than that of Cl− in land-fog events (Li et al., 1999; Raja et al., 2008; Lu et al., 2010).The ratio of Ca2+ to Na+ in the fog samples was typicallyaround 0.3, which was almost the same as the ratio of Mg2+

to Na+; however, the ratios of Ca2+/Na+ and Mg2+/Na+ inthe seawater were 0.044 and 0.23, respectively (Watanabe etal., 2006). The superabundant concentration of Ca2+ mainlycame from other anthropogenic sources, as found in studieson the sources of Ca2+, which mostly originated from soiland sand (Millet et al., 1996; Ali et al., 2004). The correla-tion coefficient between NH+4 and NO−3 was 0.91, and thatbetween NH+4 and SO2−

4 was 0.93. Meanwhile, there werealso strong relationships between H+ and NO−3 and betweenH+ and SO2−

4 . With more factories being built on DonghaiIsland for steel and oil refining programs, the level of indus-trial pollution has been increasing. The acid compounds infog-water, such as H2SO4, and HNO3, increased in 2011. Ingeneral, one would expect NH+4 and H+ to be negatively cor-related, because H+ would be consumed when it reacts withNH3 to produce NH+4 , leading to an increase in the pH. How-ever, the analysis results showed a positive correlation, indi-cating that the source of NH+4 was not from a neutralizationreaction between NH3 and H+ locally. NH+

4 can also exist inthe form of (NH4)2SO4, NH4HSO4, or NH4NO3 (Aikawa etal., 2005). In the atmosphere of a remote location, NH3 couldbe sufficiently neutralized by H2SO4, and so ammonium canoccur in sulfate compounds (Sasakawa and Uematsu, 2002).Therefore, in the present study, when the air mass was trans-ported to the observation site, the concentration of NH3 wasrelatively low, and the reaction between H+ and NH3 wasweak.

3.2. Effects of synoptic systems and trajectories on fog-water chemical compositions

Characteristics of cloud spectra, rain spectra, fog spectra,and fog water in different synoptic systems have been stud-ied intensively (Fisak et al., 2004; Niu, 2012). Błas et al.


Table 2. Correlation coefficients among different chemical speciesof sea-fog in the 13 cases. All correlation coefficients weresignificantat the 0.01 level.

Na+ H+ NH+4 K+ Ca2+ Mg2+ Cl− NO−

3 SO2−4 pH EC

Na+ 1 0.45 0.73 0.84 0.91 0.99 0.97 0.86 0.82 −0.40 0.80H+ 1 0.76 0.45 0.43 0.48 0.52 0.70 0.74 −0.83 0.85

NH+4 1 0.71 0.81 0.76 0.77 0.91 0.93 −0.65 0.92

K+ 1 0.80 0.81 0.77 0.74 0.77 −0.36 0.72Ca2+ 1 0.94 0.92 0.90 0.81 −0.31 0.79Mg2+ 1 0.99 0.90 0.82 −0.40 0.82Cl− 1 0.89 0.84 −0.43 0.84NO−

3 1 0.90 −0.55 0.95SO2−

4 −0.65 0.93pH 1 −0.71EC 1

Table 3.Ratios between different ions and the fog-water acidity in the 13 cases.

nssSO2−4 nssCa2+

Case TIC Cl−/Na+ SO2−4 /Na+ NO−

3 /Na+ K+/Na+ Ca2+/Na+ Mg2+/Na+ NO−

3 /SO2−4 (µeq L−1) (µeq L−1) pAi FA

1 5206 1.19 1.43 1.48 0.12 0.26 0.31 1.28 628.50 167.87 2.96 0.282 3571 1.37 2.06 1.65 0.14 0.43 0.32 0.88 636.12 121.81 3.11 0.323 9845 1.13 1.03 1.17 0.04 0.12 0.26 1.14 1387.82 115.92 2.61 0.524 15417 1.14 1.49 0.85 0.06 0.13 0.26 0.75 1858.37 282.35 2.670.225 20833 1.70 1.25 0.88 0.05 0.19 0.39 0.72 3013.95 524.51 2.560.226 5636 1.41 1.13 0.61 0.06 0.24 0.26 0.61 780.41 200.70 3.04 0.417 4908 1.39 1.83 0.91 0.08 0.24 0.27 0.60 762.27 102.07 3.08 0.378 12538 1.46 1.48 2.05 0.08 0.29 0.33 1.55 1170.66 311.71 2.710.299 5294 1.42 1.78 2.00 0.12 0.30 0.28 1.20 799.67 159.61 3.01 0.2510 2588 1.80 2.14 2.68 0.15 0.61 0.35 1.31 351.64 97.16 3.26 0.3911 6670 1.77 2.88 3.62 0.15 0.36 0.28 1.25 1160.15 158.14 2.690.4712 4468 1.78 2.84 3.83 0.26 0.67 0.28 1.35 724.32 98.16 3.12 0.4613 2526 1.40 2.15 1.59 0.26 0.37 0.28 0.78 469.16 58.14 3.28 0.39

Note: [nssSO2−4 ] = [SO2−

4 ]−0.12× [Na+] and[nssCa2+] = [Ca2+]−0.044× [Na+] (Keene et al., 1986; Watanabe et al., 2006); pAi=−log[nssSO2−4 +NO−

3 ]

(Hara et al., 1995); FA= [H+]/[nssSO2−4 ]+ [NO−

3 ] (Daum, 1984).

(2010) presented laws regulating fog chemistry with refer-ence to generally defined circulation indexes, and analyzedion concentrations under anticyclonic, cyclonic and transi-tional systems. Ion concentration analysis needs to considerthe effects of vertical diffusion and horizontal transportation,and synoptic systems indicate the occurrence of ascending ordescending airflow. The 13 fog cases were classified accord-ing to the prevailing synoptic systems occurring on the fogdays, and the four main types were: rearward of a high pres-sure system (cases 1, 2, 3, and 8); in front of a depression(cases 4, 5, 11, and 12); ahead of a cold front (cases 6, 7, 10,and 13); and uniform pressure field (case 9). When Zhan-jiang was rearward of a high pressure system, in front of adepression or ahead of a cold front, the frequency of sea-fogoccurrence was high (Yue et al., 2013). Therefore, the mainsynoptic systems for fog events in Zhanjiang are cold fronts,high pressure systems, and depressions.

Ion loading reflects a direct influence on pollutant scav-enging and fog-water ion concentrations (Sasakawa and Ue-

matsu, 2005). Ion loadingCair (in units of nmol m−3) can becalculated via the following equation (Igawa et al., 1991):

Cair = Cfog×LWC/ρ , (3)

in whichCfog is ion concentration andρ is water density. It isoften utilized to evaluate the efficiency of nucleation and gasscavenging in cloud or fog (Elbert et al., 2000). As shownin Fig. 3, TIC and ion loading were the lowest under a coldfront. Cold fronts usually occur at the end of a series of fogprocesses, and the pollutants would have been partly clearedaway during the fog development stage. What is more, thefrontal zone is usually associated with an updraft of cyclonicshear that is favorable for transporting pollutants to the upperlayer, which promotes the decline of ion loading and TIC.Ion loading and TIC are relatively higher under high pressuresystems, which are associated with anticyclonic circulation;the particles accumulate in the lower layer due to descendingairflow. The circulation of a depression is cyclonic, and ionloading under this type of synoptic system is a little higher


than that under a cold front. Under the weather system of adepression, the LWC is low, causing the dilution effect to beweak; so, the value of TIC is highest. At the same time, theascending motion is strong, decreasing the concentration ofpollutants.

Synoptic systems determine the prevailing wind directionand movement of airflow from one region to another. A tra-jectory model is an effective method for studying the originand horizontal transportation of air masses (Deininger andSaxena, 1997; Beiderwieden et al., 2005; Błas et al., 2010).The trajectories of the 13 cases were classified into four typesby a backward trajectory cluster analysis at the height of 1000m for 72 h (Fig. 4). The numbers of trajectory clusters were

02 0 0 04 0 0 06 0 0 08 0 0 01 0 0 0 01 2 0 0 0 T I CT ot ali onconcent rati on( TeqL X1 )

C F H P D P 02 0 04 0 06 0 08 0 01 0 0 01 2 0 0I o n l o a d i n gI onl oadi ng( nmol mX3 )

Fig. 3. TIC and ion loading under different types of synopticsystems (CF: cold front; HP: high pressure; DP: depression).

T y p e 1C a i r = 7 7 7 n m o l m � 3T I C = 6 8 4 6 � e q L � 1p H = 3 . 3T y p e 2C a i r = 2 8 5 n m o l m � 3T I C = 3 3 2 8 e q L � 1p H = 3 . 4 T y p e 3C a i r = 4 0 6 n m o l m � 3T I C = 1 2 2 8 0 e q L � 1p H = 3 . 0

T y p e 4C a i r = 2 8 6 n m o l m � 3T I C = 4 0 3 8 e q L � 1p H = 3 . 4Fig. 4. Results of backward trajectory analysis at the height of1000 m. The red line is Type 1; the dark blue is Type 2; thegreen is Type 3; and the light blue is Type 4. (Time is in UTCformat)

11, 10, 13, and 9 for the four groups. The trajectories for the13 cases moved predominantly along westward and north-ward pathways, in accordance with the surface wind direc-tions of 0◦–180◦. The ion loading in the first type (mainly incases 8, 9, and 10) was the highest. The air mass originatedfrom the northern South China Sea, then moved over the sea,and arrived at Donghai Island. Compared with other trajecto-ries, this one was shorter. The air mass was mainly affectedby industrial pollutants from the plants located in the coastalarea and oceanic aerosols. The lowest ion loading and TICappeared in the second type (mainly in cases 1, 2, 3, 6, and7) whose airflow came from the ocean to the east of Dong-hai Island. When the airflow was from north of Taiwan, itcarried moisture with low temperature, which was not pro-pitious for fog development. A low intensity of fog led tolow LWC and high TIC. Compared to the ion loading in thefirst type, the ion loading in the third type (mainly in cases 4and 5) was lower; this indicates that gravitational depositionwas prominent during long-distance transport. While the air-flow in the fourth type (mainly in cases 11–13) belonged towarm, moist airflow, which was from the southwest of Dong-hai Island and passed over central Vietnam, the ion loadingand TIC in this type were a little higher than those in thesecond type. Therefore, it is concluded that the air massestransported to Donghai Island over the sea generated differ-ent influences on fog-water ion concentrations. The total ionconcentration was lowest when the airflow was from the sea,while air masses transported from the north suppressed fogdevelopment.

It is worth noting that air masses from different wind di-rections near the surface also affected the fog-water chem-istry properties. This is a relationship highlighted previouslyby Błas et al. (2010), who reported that fog/cloud depositionmainly occurred when the wind was from the south and northat Mount Szrenica, on the Poland/Czech Republic border.Furthermore, in a study by Wrzesinsky and Klemm (2000),the major ions and metals were shown to appear under east-erly winds in central Europe. Figure 5 shows the concentra-tions of different ions from different wind directions in thepresent study. Along with the data in Table 1, it shows thatthe wind direction was predominantly easterly. Therefore,thehigh ion concentrations converged around the wind directionof 90◦ (wind direction of 0◦ represents north). When the winddirection was close to 90◦, the concentrations of Na+, Mg2+

and Cl− originating from the ocean were highest, and oceanicaerosols were primarily transported to Donghai Island alongthe wind direction of 90◦ also. The distributions of NH+4 , K+,H+, and SO2−

4 concentrations were relatively uniform whenthe wind was from the direction of 30◦–120◦, while the con-centrations of NO−3 and Ca2+ were highest when the windwas from the direction of 120◦.

3.3. Effects of meteorological elements on fog-water col-lection and TIC

The average temperature, wind speed and wind directionnear the surface for the 13 cases was 20.9◦C, 2.3 m s−1 and


05 0 01 0 0 01 5 0 005 0 01 0 0 01 5 0 0N a +N

I onconcent rati on( ÅeqL É1 ) a N E ES ESS WW N W 03 0 06 0 09 0 003 0 06 0 09 0 0I onconcentrati on( ßeqL â1 ) H +b N N E ES ESS WW N W 02 0 04 0 06 0 08 0 01 0 0 002 0 04 0 06 0 08 0 01 0 0 0I onconcentrati on( ßeqL â1 ) N H 4 +c N N E ES ESS WW N W02 04 06 08 002 04 06 08 0I onconcent rati on( �eqL �1 ) K +d N N E ES ESS WW N W 04 08 01 2 01 6 02 0 004 08 01 2 01 6 02 0 0I onconcent rati on( �eqL "1 ) C a 2 +e N N E ES ESS WW N W 05 01 0 01 5 02 0 005 01 0 01 5 02 0 0I onconcentrati on( <eqL ?1 ) M g 2 +f N N E ES ESS WW N W

04 0 08 0 01 2 0 01 6 0 004 0 08 0 01 2 0 01 6 0 0C l S

I onconcent rati on( eqLa1 ) g N N E ES ESS WW N W 05 0 01 0 0 01 5 0 02 0 0 005 0 01 0 0 01 5 0 02 0 0 0N O 3 p

I onconcent rati on( {eqL ~1 ) h N N E ES ESS WW N W 02 0 04 0 06 0 002 0 04 0 06 0 0S O 4 2 �

I onconcent rati on( �eqL�1 ) i N N E ES ESS WW N WFig. 5. Ion concentrations under different wind directions. Panels (a–i) represent the concentrations of Na+,H+, NH+

4 , K+, Ca2+, Mg2+, Cl−, NO−

3 , and SO2−4 , respectively.

74◦, with ranges of 17.2◦C–26.4◦C, 0–7.3 m s−1 and 9◦–167◦, respectively (Table 1). The wind was easterly roughly76% of the time, and the wind speed was less than 3 m s−1

roughly 74% of the time. When the wind was strong, the fog-water collection time was very long. When the wind speedrange was 1.5–2.0 m s−1, the wind direction range was 79◦–90◦, and the temperature range was 20.0◦C–21.0◦C; the max-imum numbers of fog-water samples were 47, 48 and 45, re-spectively (Fig. 6). These were the conditions favorable forfog development. The average collection time for one sam-ple in this study was 48.4 min; and for comparison, the col-lection time for one sample in Nanjing was 322 min (Lu etal., 2010). The collection efficiencies (in units of mL min−1)calculated by collection volume and collection time for the13 cases were 0.94, 0.86, 0.18, 0.54, 0.83, 0.37, 0.42, 1.15,1.03, 1.07, 0.33, 1.03, and 0.87 mL min−1, respectively. Itis apparent that the collection efficiency decreased with in-creasing wind speed (Fig. 6a). The volume of fog-water insamples was small at low wind speeds, similar to the obser-vational results at Mt. Tateyama, near the coast of Japan,reported by Watanabe et al. (2010).

The variation of TIC with wind speed, wind direction andtemperature was similar to that of collection time. Statisti-cal analysis shows that the correlation coefficient betweencollection time and TIC reached 0.62, with the confidence

level at 99% (α = 0.01). The wind speed, wind directionand temperature intervals corresponding to maximum TICwere 3.5–4.0 m s−1, 79◦–90◦ and 21.0◦C–22.0◦C, respec-tively. The diffusion of pollutants needed the presence ofwind, so a suitable wind speed and direction could ensurethe pollutants reached the observation site. The variationofTIC was not conspicuous in terms of wind direction, and theion concentration was lowest for wind directions of 23◦–34◦

and 124◦–135◦. However, when the temperature was higherthan 22.0◦C, TIC decreased sharply. Warm, moist airflowwould be strengthened when the temperature difference atthe air–sea interface increased. This was propitious for fogdevelopment and shortened the collection time. Examinationof the influence of meteorological conditions on fog-wateracidity indicated that pH was low at high wind speeds andlow temperatures (19.0◦C–20.0◦C), while pH values rose athigher temperatures and during southeasterly winds. Almostno factories exist in the southeast of the observation site,sothe concentration of pollutants was low with high pH.

3.4. Effects of microphysical factors on the chemical com-position of sea-fog

Fog-water ion concentration not only depended on thepollutants suspended in the atmosphere but were also af-fected by microphysical characteristic quantities. The ranges


0 1 2 3 4 5 61 0 01 0 0 01 0 0 0 0 T I CTIC( ²eqL¶1 )

02 04 06 08 01 0 0S a m p l e s n u m b e rS ampl esnumb er

3 . 03 . 54 . 04 . 5p H pH05 01 0 01 5 02 0 0C o l l e c t i o n t i m e C oll ecti onti me( mi n)0 . 00 . 51 . 01 . 52 . 0 C o l l e c t i o n e f f i c i e n c y

C oll ecti oneffi ci ency(L/ mi n)W i n d s p e e d ( m s � 1 )

1 0 01 0 0 01 0 0 0 01 0 0 0 0 0 T I CTIC( �eqL �1 )

02 04 06 08 01 0 0S a m p l e s n u m b e rS ampl esnumb er

3 . 03 . 54 . 04 . 55 . 05 . 5p H pH2 0 4 0 6 0 8 0 1 0 0 1 2 0 1 4 0 1 6 00 . 00 . 20 . 40 . 60 . 81 . 01 . 21 . 41 . 61 . 82 . 0 C o l l e c t i o n e f f i c i e n c y

C oll ecti oneffi ci ency(L/ mi n)W i n d d i r e c t i o n ( ° ) 05 01 0 01 5 02 0 0C o l l e c t i o n t i m e

C oll ecti onti me( mi n)

1 8 1 9 2 0 2 1 2 2 2 3 2 4 2 5 2 6 2 71 0 01 0 0 01 0 0 0 0 T I CTIC( oeqL s1 )

02 04 06 08 01 0 0S ampl esnumb erS a m p l e s n u m b e r

3 . 03 . 54 . 04 . 55 . 0 pHp H0 . 60 . 81 . 01 . 21 . 4 C o l l e c t i o n e f f i c i e n c y

C oll ecti oneffi ci ency(L/ mi n)T e m p e r a t u r e ( ) 2 03 04 05 06 07 08 09 0

C oll ecti onti me( mi n)C o l l e c t i o n t i m e

a

bc

Fig. 6. Variations of collection elements, TIC and pH under different meteorologicalconditions. The collection elements include collection time, collection efficiency, andnumber of samples: (a) variation of average values for different quantities with respectto wind speed (with an increment of 0.5 m s−1); (b) variation with respect to wind di-rection (with an increment of 11.25◦); (c) variation with respect to temperature (withan increment of 1◦C). The “whiskers” extending from the black boxes representthestandard deviation of TIC.

of fog droplet number concentration (N), LWC, average ra-dius (r), and surface area (S) per volume of air were 119–372cm−3, 0.017–0.170 g m−3, 1.71–3.28µm, and 0.011–0.073m2 m−3, respectively. The extent of the influence of micro-physical quantities on fog-water ion concentration needs tobe discussed using the relationships between microphysicalcharacteristic quantities and ion concentrations.

Researchers have attempted to find out the characteristicquantities that reflect the variation of TIC. The ratio of sur-face area to volume reflects the scavenging efficiency of cloud

droplets (Dore et al., 1992). Therefore, the ratio of surfaceand volume can be calculated with the following equation:

SV

=4π×10−6∑n(r)r2dr43π×10−6∑n(r)r3dr

, (4)

wheren(r) is the number concentration of fog droplets atdifferent radiusr, is regarded as an important microphysi-cal characteristic factor to be considered. Since the ratioofS andV is given byS/V = 3/r, the discussion ofS/V could


be simply replaced by 1/r. For a given droplet size, the con-centration of liquid phase is governed by chemical speciesconcentration and the number of droplets in the atmosphere.An increased concentration of small droplets would result ina higher surface/volume ratio, promoting the exchange be-tween gas and liquid (Schwartz, 1988; Millet et al., 1996).LWC reflects the degree of fog-water dilution. Li et al. (2008)reported TIC as having negative correlations withr and LWC,with correlation coefficients of−0.71 and−0.60, respec-tively. Moller et al. (1996) presented a general power lawrelationship between LWC and the chemical composition ofcloud water, similar to the result of Elbert et al. (2000). Todescribe the scavenging potential,S/LWC was calculated toillustrate the effects of fog absorption and dilution (Lu etal.,2010).

Using the results mentioned above, we can examine therelationships between these characteristic quantities and TIC.The correlations of TIC withS/LWC, 1/r, and visibility (Vis)for all samples were 0.44, 0.45, and 0.48, respectively, a lit-tle better than those with the other characteristic quantitiessuch asS, LWC, andN. In individual cases, the correlationcoefficients increased obviously. As shown in Figs. 7a and7b, the average ion concentration increased withS/LWC and1/r, albeit with large fluctuations, usually spanning one orderof magnitude, especially whenS/LWC and 1/r were 0.4–0.7m2 g−1 and 0.3–0.5µm−1, respectively. Most fog-water sam-ples were taken when the visibility was below 200 m, and thevisibility at which the fog-water could be collected did notexceed 700 m (Fig. 7c), which might have been caused by

the deposition of larger fog droplets; and the longer the fogperiod lasted, the more deposition flux there was (Klemm andWrzesinsky, 2007). In the discussion above, the low correla-tion coefficient for the least-squares fit illustrates thesechar-acteristic quantities could not present the variation of TICon Donghai Island. So, we searched for another character-istic quantity, which was more suitable to establish the pa-rameterization formula for all fog-water samlples. In viewof the scavenging effect based on microphysical characteris-tic quantities, the combination quantity Lr= 1/(LWC× r) isproposed, which can comprehensively reflect scavenging ef-ficiency (1/r) and dilution effect (LWC). The aerosols andgases in the atmosphere will enter fog droplets to increasethe chemical species and fog-water ion concentrations. Thisis affected by processes at the air–liquid interface. Sincetheratio of S andV can be simply expressed by 1/r, it makesusing 1/r to reflect the scavenging potential more compre-hensive when considering the volume of fog droplets. LWCandS are the most important factors in collection efficiency;the correlation coefficients between them and collection ef-ficiency were 0.75 and 0.73, respectively. Furthermore, ahigher LWC would be associated with lower ion concentra-tion, when the aerosol concentration does not change signif-icantly. Taking scavenging efficiency and the dilution effectinto consideration, we have Lr to compare with TIC. The av-erage correlation coefficient between Lr and TIC for all thesamples was 0.74 (Fig. 7d), indicating an improvement ofthe fitting. Therefore, Lr has more predictive power than 1/ror S/LWC alone, so it was used in the least-squares fitting

0 . 2 0 . 4 0 . 6 0 . 8 1 . 0 1 . 21 0 01 0 0 01 0 0 0 0aS / L W C 0 . 2 µ 0 . 3TIC( » eqL¿1 )

S / L W C ( m 2 g Ë 1 ) 0 . 3 Ñ 0 . 40 . 4 Ñ 0 . 50 . 5 Ñ 0 . 60 . 6 Ñ 0 . 70 . 7 Ñ 0 . 80 . 8 Ñ 1 . 1y = Ú 4 7 0 8 + 2 1 8 6 0 xR = 0 . 4 1 0 . 1 0 . 2 0 . 3 0 . 4 0 . 5 0 . 6 0 . 71 0 01 0 0 01 0 0 0 0 1 / r 0 . 1 ñ 0 . 2TIC( ö eqLú1 )

1 / r ( � m � 1 ) b0 . 2 ñ 0 . 30 . 3 ñ 0 . 40 . 4 ñ 0 . 50 . 5 ñ 0 . 7 y = 7 8 4 9 + 3 5 7 3 6 xR = 0 . 4 2

0 1 0 0 2 0 0 3 0 0 4 0 0 5 0 0 6 0 0 7 0 01 0 01 0 0 01 0 0 0 0cV i s 3 0 # 6 0TIC( (eqL,1 )

V i s ( m ) 6 0 # 1 0 01 0 0 # 2 0 02 0 0 # 4 0 04 0 0 # 7 0 0y = 1 4 9 1 + 3 9 xR = 0 . 4 6 0 2 0 4 0 6 0 8 0 1 0 0 1 2 01 0 0 01 0 0 0 0TIC( KeqLO1 )1 / ( L W C × r ) ( [ m ] 1 m 3 g ] 1 )y = 2 3 4 8 + 4 3 8 xR = 0 . 7 4 2 m 44 m 1 01 0 m 2 0 d2 0 m 4 04 0 m 1 2 21 / ( L W C × r ) 0 . 2 5 m 2

Fig. 7. Relationships between TIC and different characteristic quantities: (a)S/LWC; (b) 1/r; (c) Vis; and (d) 1/(LWC× r).


analysis. Furthermore, a power law formula was constructed:TIC= a(LWC−1r−1)b, and the least-squared values for thefitting parametersa andb were 1053 and 0.82, respectively.The coefficienta is related to the ion concentration, andb de-termines the shape of the function. For the 13 cases exceptcases 6 and 10, the range ofa was 323–3084, and that ofbwas 0.26–1.37. Therefore, Lr could act as an indicator char-acteristic quantity to build a parameterization relation withTIC. More observational data is needed to examine whetheror not the variation in the range can fit other cases.

3.5. Effects of aerosols on fog-water chemical composi-tions

Suspended aerosol particles could affect fog-water ioncomposition (Hoag et al., 1999; Sasakawa and Uematsu,2002). Therefore, studying aerosol number concentrationsand spectra help our understanding of aerosols’ influence onthe chemical composition of fog-water.

Figure 8 shows the Air Pollution Index (API) values fora few cities in China on 19–24 March 2010. It is based ondata from the Ministry of Environmental Protection of thePeople’s Republic of China, and reflects concentrations ofSO2, NO2 and PM10. On 20 March, Beijing was affectedby dust aerosols, with the API reaching 500. Then, Nanjingand Changsha in central China were subsequently affected.On 22 March, the API in Xiamen, a southeast coastal area ofChina, reached its maximum. The dust process was over on24 March.

The average aerosol spectrum was unimodal with a peakradius of about 0.02–0.1µm, and the maximum diameterwas smaller than 6µm. The fog-water chemical composi-tions also depended on the species and sizes of aerosol par-ticles. The ratio of Ca2+/Na+ in fog-water was nearly 2–10 times more during 22–23 March than in the other casesin 2010 (Yue et al., 2012), and Ca2+ was mainly from soiland dust. There was a strong dust storm in Inner Mongo-lia on 19 March, carrying a large amount of dust particles toSoutheast China. This dust storm changed the aerosol com-position in the coastal area of the South China Sea. Sandsediments appeared in the fog-water samples collected dur-ing 22–23 March, and the aerosol spectra broadened in this

case. The aerosol number density concentration of diameterlarger than 1µm on 22–23 March was higher than that inthe other cases (Fig. 9). Fine particles with diameter smallerthan 2.1µm were mainly composed of NH+4 , K+, Cl−, NO−

3 ,PO3−

4 , and SO2−4 , while Na+, Mg2+, Ca2+, and F− were en-

riched in the particles of larger drop size (Raja et al., 2008;Liu et al., 2012). The number concentration of large aerosolparticles increased when the dust storm passed through, sug-gesting that the concentrations of Mg and Ca increased. Thedust aerosols originated from the drought and semiarid re-gions of northern China, existing in the form of CaCO3. Dur-ing the long-distance transport of dust aerosols, Mg and Careacted with pollutants such as SO2 and NOx, and their prod-ucts entered the fog droplets (Xue et al., 2011). The TIC on24 March was the lowest (Yue et al., 2012), correspondingto the lowest aerosol concentration (1106 cm−3). It was ap-parent that gravitational settling during the dust transithad ascavenging effect. In fact, the average aerosol concentrationon non-fog days on Donghai Island was 7298 cm−3, higherthan that of 4463 cm−3 on fog days. This confirms that dur-ing the fog period aerosols could be removed partly by fogdroplets (Yuskiewicz et al., 1998; Pant et al., 2010).

4. Conclusions

(1) During the sea-fog observation in 2011, a total of 191fog-water samples were collected. These samples were largeenough for carrying out statistical analysis of different influ-encing factors. The average values of pH and EC were 3.34and 505µS cm−1, respectively, with a negative correlationcoefficient of−0.87. The pH values were almost the sameas those measured in the eastern South Pacific Ocean. NH+

4 ,NO−

3 , and SO2−4 played more improtant roles in affecting pH

than the other ions. The average cation and anion concentra-tions for the 13 cases were 2630 and 2970µeq L−1, respec-tively. Na+ and Cl− originated from oceanic aerosols, andtheir concentrations were larger than other ions in the sam-ples with higher TIC.

(2) The analysis of ion concentrations was combined withvertical diffusion and horizontal transportation. Ion loadingand TIC under a cold front were the lowest, as compared with

1 9 2 0 2 1 2 2 2 3 2 401 0 02 0 03 0 04 0 05 0 0 B e i j i n gN a n j i n gC h a n g s h aX i a m e nG u a n g z h o uZ h a n j i a n gAPI D a t aFig. 8. Variation of API with time from 19 to 24 March.


0 1 2 3 4 5 6 7 8 9 1 01 E ¢ 41 E ¢ 30 . 0 10 . 111 01 0 01 0 0 01 0 0 0 01 0 0 0 0 00 1 2 3 4 5 6 7 8 9 1 01 E ¢ 41 E ¢ 30 . 0 10 . 111 01 0 01 0 0 01 0 0 0 01 0 0 0 0 0

0 1 2 3 4 5 6 7 8 9 1 01 E ¢ 41 E ¢ 30 . 0 10 . 111 01 0 01 0 0 01 0 0 0 01 0 0 0 0 00 1 2 3 4 5 6 7 8 9 1 01 E ¢ 41 E ¢ 30 . 0 10 . 111 01 0 01 0 0 01 0 0 0 01 0 0 0 0 0

N umb erd esit yconcent rati on( cm´3 ¶m¸1 ) 2 2 M a r 2 2 1 2 L S T Ã 2 3 M a r 1 0 0 3 L S T 2 3 M a r 2 3 0 0 L S T Ã 2 4 M a r 1 0 0 0 L S T3 1 M a r 1 8 5 0 L S T Ã 1 A p r 0 6 2 0 L S T 1 A p r 1 8 3 7 L S T Ã 2 A p r 0 6 1 5 L S T

D ( Ï m )Fig. 9. Aerosol spectra for four fog cases in 2010.

those under a high pressure system or depression. In terms ofthe origin and horizontal transportation of air masses, thosefrom a short distance were mainly affected by pollutants dis-charged from industrial plants in the coastal area, so ion load-ing was the highest. The total ion concentration and ionloading were lowest when the airflow was from the sea. Airmasses from the north suppressed fog development.

(3) Fog-water may have different characteristics due tometeorological conditions. The average temperature, windspeed and wind direction for the 13 cases was 20.9◦C, 2.3m s−1 and 74◦, respectively. The collection efficiency de-creased with increasing wind speed. The wind speed, winddirection and temperature ranges corresponding to the max-imum TIC were 3.5–4 m s−1, 79◦–90◦ and 21◦C –22◦C, re-spectively. The concentrations of Na+, Mg2+ and Cl− thatoriginated from the ocean were highest when the prevail-ing wind was from the ocean to the east of Donghai Island.When the temperature was higher than 22◦C, TIC decreasedsharply. The pH value was low at high wind speeds and tem-peratures in the range of 19◦C–20◦C.

(4) Ion concentrations can be affected by many processes,including concentrations of pollutants, microphysical charac-teristic quantities, and so on. The correlations of TIC withS/LWC, 1/r, or Vis were relatively stronger than those withother characteristic quantities. The average ion concentrationincreased withS/LWC and 1/r. Most fog-water samples weretaken when the visibility was below 200 m. In view of the lowcorrelation coefficient between microphysical characteristicquantities and TIC, a new parameter Lr = 1/(LWC× r) wasproposed to better reflect the scavenging efficiency (1/r) anddilution effect (LWC). The correlation coefficient betweenLrand TIC reached 0.74. A formula for TIC= a(LWC−1r−1)b

was obtained, where the fitting parametersa andb are 1053and 0.82, respectively.

(5) The fog-water chemical composition also dependedon the species and size of aerosol particles. The ratio ofCa2+/Na+ in fog-water was nearly 2–10 times more on 23March than in the other cases in 2010. When a dust stormpassed through, the number concentrations of large aerosolparticles, such as Mg and Ca with diameter larger than 1µm, increased. The average aerosol concentration on non-fogdays was 7298 cm−3, much higher than that of 4463 cm−3

on fog days, which confirms that aerosols could be removedpartly by fog droplets.

Acknowledgements. Funding for this work was provided bythe Meteorology Fund of the Ministry of Science and Technology[Grant No. GYHY(QX)2007-6-26], the National Natural ScienceFoundation of China (Grant Nos. 41275151 and 41375138), thePriority Academic Program Development of Jiangsu Higher Educa-tion Institutions, and the Graduate Student Innovation Plan at theUniversities of Jiangsu Province.

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