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Precipitation Chemistry and Corresponding Transport Patterns of Influencing Air Masses at Huangshan Mountain in East China

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doi: 10.1007/s00376-014-3189-1

  • One hundred and ten samples of rainwater were collected for chemical analysis at the summit of Huangshan Mountain, a high-altitude site in East China, from July 2010 to June 2011. The volume-weighted-mean (VWM) pH for the whole sampling period was 5.03. SO42- and Ca2+ were the most abundant anion and cation, respectively. The ionic concentrations varied monthly with the highest concentrations in winter/spring and the lowest in summer. Evident inter-correlations were found among most ions, indicating the common sources for some species and fully mixing characteristics of the alpine precipitation chemistry. The VWM ratio of [SO42-]/[NO3-] was 2.54, suggesting the acidity of rainwater comes from both nitric and sulfuric acids. Compared with contemporary observations at other alpine continental sites in China, the precipitation at Huangshan Mountain was the least polluted, with the lowest ionic concentrations. Trajectories to Huangshan Mountain on rainy days could be classified into six groups. The rainwater with influencing air masses originating in Mongolia was the most polluted with limited effect. The emissions of Jiangxi, Anhui, Zhejiang and Jiangsu provinces had a strong influence on the overall rain chemistry at Huangshan Mountain. The rainwater with influencing air masses from Inner Mongolia was heavily polluted by anthropogenic pollutants.
    摘要: One hundred and ten samples of rainwater were collected for chemical analysis at the summit of Huangshan Mountain, a high-altitude site in East China, from July 2010 to June 2011. The volume-weighted-mean (VWM) pH for the whole sampling period was 5.03. SO42- and Ca2+ were the most abundant anion and cation, respectively. The ionic concentrations varied monthly with the highest concentrations in winter/spring and the lowest in summer. Evident inter-correlations were found among most ions, indicating the common sources for some species and fully mixing characteristics of the alpine precipitation chemistry. The VWM ratio of [SO42-]/[NO3-] was 2.54, suggesting the acidity of rainwater comes from both nitric and sulfuric acids. Compared with contemporary observations at other alpine continental sites in China, the precipitation at Huangshan Mountain was the least polluted, with the lowest ionic concentrations. Trajectories to Huangshan Mountain on rainy days could be classified into six groups. The rainwater with influencing air masses originating in Mongolia was the most polluted with limited effect. The emissions of Jiangxi, Anhui, Zhejiang and Jiangsu provinces had a strong influence on the overall rain chemistry at Huangshan Mountain. The rainwater with influencing air masses from Inner Mongolia was heavily polluted by anthropogenic pollutants.
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Manuscript History

Manuscript received: 17 September 2013
Manuscript revised: 20 December 2013
通讯作者: 陈斌, bchen63@163.com
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Precipitation Chemistry and Corresponding Transport Patterns of Influencing Air Masses at Huangshan Mountain in East China

    Corresponding author: SHI ChunE; 
  • 1. Anhui Institute of Meteorological Sciences, Key Laboratory for Atmospheric Sciences and Remote Sensing of Anhui Province, Hefei 230031;
  • 2. State Key Laboratory of Atmospheric Boundary Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029;
  • 3. Key Laboratory of Atmospheric Composition and Optical Radiation, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031
Fund Project:  The authors appreciate Peter HYDEs comments and careful proofreading. Prof. TANG Jie and XU Xiaobin provided disposable nylon-polyethylene bags for sampling. This work was supported by funds from the Scientific Research Projects of High-level Talents of the Department of Human Resources and Social Security of Anhui Province (Grant No. 2009Z019) and the State Key Laboratory of Atmospheric Boundary Physics and Atmospheric Chemistry (Grant No. LAPC-KF-2011-05). The authors thank colleagues at the Huangshan Meteorological Office for their assistance with sample collection.

Abstract: One hundred and ten samples of rainwater were collected for chemical analysis at the summit of Huangshan Mountain, a high-altitude site in East China, from July 2010 to June 2011. The volume-weighted-mean (VWM) pH for the whole sampling period was 5.03. SO42- and Ca2+ were the most abundant anion and cation, respectively. The ionic concentrations varied monthly with the highest concentrations in winter/spring and the lowest in summer. Evident inter-correlations were found among most ions, indicating the common sources for some species and fully mixing characteristics of the alpine precipitation chemistry. The VWM ratio of [SO42-]/[NO3-] was 2.54, suggesting the acidity of rainwater comes from both nitric and sulfuric acids. Compared with contemporary observations at other alpine continental sites in China, the precipitation at Huangshan Mountain was the least polluted, with the lowest ionic concentrations. Trajectories to Huangshan Mountain on rainy days could be classified into six groups. The rainwater with influencing air masses originating in Mongolia was the most polluted with limited effect. The emissions of Jiangxi, Anhui, Zhejiang and Jiangsu provinces had a strong influence on the overall rain chemistry at Huangshan Mountain. The rainwater with influencing air masses from Inner Mongolia was heavily polluted by anthropogenic pollutants.

摘要: One hundred and ten samples of rainwater were collected for chemical analysis at the summit of Huangshan Mountain, a high-altitude site in East China, from July 2010 to June 2011. The volume-weighted-mean (VWM) pH for the whole sampling period was 5.03. SO42- and Ca2+ were the most abundant anion and cation, respectively. The ionic concentrations varied monthly with the highest concentrations in winter/spring and the lowest in summer. Evident inter-correlations were found among most ions, indicating the common sources for some species and fully mixing characteristics of the alpine precipitation chemistry. The VWM ratio of [SO42-]/[NO3-] was 2.54, suggesting the acidity of rainwater comes from both nitric and sulfuric acids. Compared with contemporary observations at other alpine continental sites in China, the precipitation at Huangshan Mountain was the least polluted, with the lowest ionic concentrations. Trajectories to Huangshan Mountain on rainy days could be classified into six groups. The rainwater with influencing air masses originating in Mongolia was the most polluted with limited effect. The emissions of Jiangxi, Anhui, Zhejiang and Jiangsu provinces had a strong influence on the overall rain chemistry at Huangshan Mountain. The rainwater with influencing air masses from Inner Mongolia was heavily polluted by anthropogenic pollutants.

1. Introduction
  • Precipitation chemistry involves numerous physical and chemical mechanisms of atmospheric components, and thus can reflect the transport/transformation of anthropogenic pollutants related to regional precipitation acidification (\"Ozsoy et al., 2008). Precipitation chemistry at alpine stations, because of their high elevations, reflects the characteristics of regional air quality, as well as the effects of long-range transport. Thus, research on precipitation chemistry at high mountain peaks generally sheds more light on regional atmospheric pollution than do lower-elevation sites. Such high-elevation sites have attracted much attention in Europe and North America since the 1980s (Menz and Seip, 2004). To date, considerable attention has been focused on the wet deposition of acidic species and their related effects on high-altitude ecosystems (Aleksic et al., 2009).

    In China, precipitation chemistry monitoring at alpine stations started in 1980s. As shown in Fig. 1, precipitation chemistry has been monitored and studied at various Chinese alpine stations since the 1980s, including Waliguan Mountain in Qinghai Province (Tang et al., 2000), Tianshan Mountains in Xinjiang Uygur Autonomous Region (Zhao et al., 2008), Mount Tai in Shandong Province (Wang et al., 2008), Jade Dragon Snow Mountain in Yunnan Province (Liu et al., 1993), Mount Emei (Xue and Schnoor, 1994) in Sichuan Province, Leigong Mountain (Aas et al., 2007) in Guizhou Province, Hengshan Mountain in Hunan Province (Sun et al., 2010), Lushan Mountain in Jiangxi Province (Li et al., 2012), Mangdang Mountain in Fujian Province (Cheng et al., 2011), and Lulin Mountain in Taiwan (Wai et al., 2008). Based on the measurements at these sites, precipitation is acidic at all alpine stations except Tianshan Mountains, where it is alkaline, and Waliguan Mountain, where it is near neutral. SO42- is the dominant anion and NH4+ (or Ca2+) is the dominant cation. In addition, long-term monitoring of precipitation chemistry at some mountain sites has revealed increasing acidity and decreasing [SO42-]/[NO3-] ratios, e.g., at Lushan Mountain (Li et al., 2012).

    Figure 1.  Locations of the precipitation chemistry sampling stations at high-altitude mountains in China: 1 Tianshan Mountains; 2 Waliguan Mountain; 3 Mount Tai; 4 Jade Dragon Snow Mountain; 5 Mount Emei; 6 Leigong Mountain; 7 Hengshan Mountain; 8 Lushan Mountain; 9 Huangshan Mountain; 10 Mangdang Mountain; 11 Lulin Mountain; XJ, XinJiang; NM, NeiMeng; HB, Hebei; SX, ShanXi; QH, QingHai; SC, SiChuan; HN, HeNan; SD, ShanDong; JS, JiangSu; AH, AnHui; HB2, HuBei; HN2, HuNan; GZ, GuiZhou; YN, YunNan; GX, GuangXi; GD, GuangDong; FJ, FuJian; ZJ, ZheJiang; TW, Taiwan.

    Huangshan Mountain is the highest mountain close to the Yangtze River Delta. Although short-term measurements of precipitation chemistry were conducted in the mid 1980s (Huang et al., 1993), more recent studies on the characteristics of precipitation chemistry in this area are absent. In view of the unique environmental setting, high elevation, low local emissions, and proximity to the bustling Yangtze River Delta, we conducted a year-round field study at Huangshan Mountain. We did this to characterize the rainwater chemistry in the free troposphere over East China, and relate it to transport patterns. To achieve this goal, we analyzed one full year of data and compared the rainwater chemistry with other alpine sites located in different parts of the world. Finally, we determined the transport patterns by back-trajectory cluster analysis to understand how the rain chemistry at Huangshan Mountain varied with them.

2. Sampling site and methods
  • As shown in Fig. 1, Huangshan Mountain (also named Yellow Mountain), the highest mountain in East China, is located in southern Anhui Province. It covers around 1200 km2, with several summits >1800 m MSL. The monitoring site is within the Bright Top Weather Station (BTWS) [(30°08'N, 118°09'E); 1840.4 m MSL], at the second highest summit of Huangshan Mountain. Far from urban areas, the closest city, Huangshan City, is medium-sized (population: 500 000), located in southern Anhui Province, 67 km away but 1700 m lower. No prominent emission source exists within 50 km. Regionally, Huangshan Mountain is 300 km from the Yangtze River Delta economic region centered in Shanghai. Thus, Huangshan Mountain has become one of the areas in China most impacted by acid deposition.

    Established in 1955 by the China Meteorological Administration (CMA), BTWS had an annual average rainfall during the latest 30 years of 2257 mm (maximum: 3227 mm; minimum: 1687 mm). In 1989, the CMA set up the acid rain monitoring site at BTWS, routinely measuring precipitation pH and electronic conductivity (EC, also referred to as "K-value"). According to the Standard Operation Manual for Acid Rain Monitoring (CMA, 2005), precipitation samples were collected manually every rainy day using a cleaned polyethylene bucket. All samples with daily rainfall over 1 mm were analyzed on-site for their pH and K-value with PHS-3B and DDS-307 instruments manufactured by Shanghai Rex Instruments. Full-time meteorological observers took charge of sampling and on-site measurements. Twenty-four-hour samples were collected from 0800 BST (Beijing Standard Time) (0000 UTC) each day. When it began to rain, the sampling bucket was positioned by the observer on duty. Between events on the same sampling day, the sampler was covered and stored inside. According to measurements from 2006 to 2011, Huangshan Mountain received most rainfall in summer, followed by spring, and least in winter. The precipitation acidity varied seasonally, with more and stronger acid rain in winter. The volume weighted mean (VWM) pH showed the sequence to be summer > autumn > spring > winter, while the VWM K-value had the reverse sequence of pH (Shi et al., 2013).

  • From July 2010 to June 2011, 110 parallel precipitation samples were collected for chemical analysis on a daily basis. The total rainfall of the 110 samples was 2436 mm, close to the annual average of the past 30 years. Among them, samples from October 2010 to June 2011 were collected in disposable nylon-polyethylene bags lined in the polyethylene sampling buckets (inner diameter: 36 cm). The others were collected in clean, dry polyethylene sampling buckets. To obtain enough rain for chemical analysis for each rain event, two polyethylene buckets were used. The buckets were fastened to metal shelves on cement pillars with the bucket opening at a height of around 1.0 m above the ground. After collection, the samples were put in the lab and a small portion of each sample was taken out for measurement of pH and K-value. The remainder was transferred into cleaned 500-ml polyethylene bottles and stored in the refrigerator at 4°C. The samples were transported at this temperature to Anhui Institute of Geological Experiment in Hefei for chemical analysis every month or half-month.

    Anions (SO42-, NO3-, Cl-), cations (K+, Na+, Ca2+, Mg2+, NH4+), pH, and EC were determined in the lab. K+, Na+, Ca2+, Mg2+ and SO42- were measured by Inductivity Coupled Plasma-Atomic Emission Spectrometry (ICP-AES), a Thermo Fisher Scientific ICAP6300 spectrometer. NO3- and NH4+ were measured by colorimetry. The detection limits for cations (K+, Na+, Ca2+, Mg2+, NH4+) and anions (SO42-, NO3-, Cl-) were 2.56, 2.17, 1.50, 1.23 and 1.43 μeq L-1, and 2.08, 3.22 and 56.33 μeq L-1, respectively. Cl- was measured by a volumetric method with very high detection limits. HCO3- was estimated based on the pH level (WMO GAW Precipitation Chemistry Science Advisory Group, 2004). To avoid interferences, no filtering of the samples was conducted. This may have induced some errors, e.g., the overestimation of some ion concentrations, such as Ca2+.

    For the on-site measurements of pH and K-value, quality assurance (QA) and quality control (QC) procedures were strictly followed (CMA, 2005). The station participated in annual blind sample tests (Tang et al., 2008) and passed all of them. For sample collection, the QA consisted of the following: the instruments for sampling (e.g., the funnel, buckets, and the 500-ml polyethylene flask) were first cleaned using clear water, and then cleansed several times using pure water before being dried off ahead of their next use. To avoid any interference by dry deposition, the buckets were positioned as soon as the rain began, and then taken inside and covered when the rain stopped. All the operators were full-time professional weather observers. During transportation, the samples were kept at a low temperature. For the laboratory measurements of ion compositions, internal QC was as follows. Pure water was used for cleaning and solution preparation. Standard samples were prepared using standard materials traceable to China National Standards and blank samples were used for constructing calibration curves for each batch of samples.

    Since there were uncertainties in the concentrations of Cl- and Ca2+, the ion balance method recommended by the World Meteorological Organization's Global Atmosphere Watch (WMO-GAW) was inappropriate for the QC of our samples. Instead, two steps were conducted: first, Wright's rule was used to discard data with a very large Ca2+ concentration. Accordingly, three records were discarded, which accounted for only 0.36% of the total rainfall of that period. Then, regression analyses were conducted between the laboratory measured (K m) and calculated (K c) K-values, and between total anions (TA) and total cations (TC) for the QC of the data. In the second step, two schemes were adopted. In scheme 1, TA and TC were calculated as follows:

    where [X] is the equivalent concentration of ion X in units of μeq L-1. All ionic concentrations below the method detection limit were set to one half of the limit. The K c value was calculated for each sample using the formula recommended by the WMO-GAW's Precipitation Chemistry Science Advisory Group (2004). In scheme 2, the contribution of Cl- was deleted in TA and K c.

    For each scheme, Wright's rule was used once to discard some outlying data by regression analysis between TA and TC, and K m and K c, respectively. In the regression analysis, setting a variable as a dependent variable, when the difference between the measured and estimated values exceeded a control limit, the data were assumed as outlying data. The control limit was defined as three standard deviations (σ) of differences. Then, correlation coefficients between TA and TC, and between K m and K c, were calculated for those retained records. Ultimately, the results of scheme 1 using correlation between TA and TC were the best, because they had the highest correlation coefficients between TA and TC, and K m and K c, the largest slope in the regression equation between TA and TC, and the most records retained. After the two-step QC check of the data was performed, 106 samples (96.4% of the total samples) were retained. The total rainfall of the retained samples accounted for 99.0% of the accumulated rainfall.

    For those retained sample records, K c was highly correlated with K m, with a correlation coefficient (r) of 0.96; while K c was generally higher than K m, with a mean bias (MB) of 5.2 μS cm-1. The high correlation coefficient between K m and K c suggested that the analyzed ions covered most ions in the rain. TA was also highly correlated with TC (r=0.93), although the slope (0.72) was much lower than 1 and the intercept was quite high (52.61 μeq L-1). TA was generally higher than TC, with a positive mean bias (MB = 2.72 μeq L-1) and a VWM ratio of TA/TC over unit (1.13), which is unreasonable since we did not measure the organic acid in rain. In addition, the K c was higher than K m, which was also unreasonable, since the measured items could not cover all ions in the rainwater. After examining all the measurement methods, we determined that Cl- was the most likely to be overestimated. Based on the 106 retained samples, the VWM concentration of Cl- was 63 μeq L-1, which was extremely high and inexplicable at an inland alpine site.

  • To investigate the influence of different source regions on the precipitation chemistry at Huangshan Mountain, back-trajectory cluster analyses (Brankov et al., 1998) were conducted. The 72-h air mass backward trajectory was calculated for each retained rain event using the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) version 4.8, developed by the National Oceanic and Atmospheric Administration (NOAA) Air Resources Laboratory (http://www.arl.noaa.gov/ready/hysplit4.html) (Draxler, 1997), together with Global Data Assimilation System (GDAS) data downloaded from the NOAA website (ftp.arlhq. noaa.gov/pub/archives/). The original time was the middle of the rain event and the original height was set to 1000 m AGL, corresponding to about 860 hPa in the area by the GDAS dataset, which was close to the normal surface pressure at BTWS.

    All back-trajectories on the 106 retained rain days were categorized into six groups using the method put forward by (Dorling et al., 1992). The distribution of cluster-mean trajectories was obtained by merging all trajectories in a group (see the following section). Based on the results of clustering, the VWM ion concentrations, pH values and K-values were calculated for samples in each group.

3. Results and discussion
  • Table 1 shows the species VWM concentrations for the entire sampling period. The year-round VWM pH value was 5.03——a little lower than the pH value of typical natural rainwater, which is 5.6. Furthermore, the value was higher than those measured in recent years at other alpine sites in East China, e.g. at Mount Tai (Wang et al., 2008) and Lushan Mountain (Li et al., 2012), but lower than that measured at a higher island site in Taiwan, Lulin Mountain (Wai et al., 2008). The most abundant acidic and alkaline species were SO42- (33.0 μeq L-1) and Ca2+ (51.2 μeq L-1), respectively, followed by NH4+ (25.6 μeq L-1) and NO3- (13.0 μeq L-1). This suggests that the alkaline cations (Ca2+, NH4+) exceeded the strong acidic anions (SO42-, NO3-), and there should be some other anions, e.g., Cl- and organic acid, in the rainwater. Other species concentrations (K+, Na+, Mg+) were low because of the high altitude.

    The equivalent ratios of [SO42-]/[NO3-] (abbreviated as R sn), ([Ca2+]+[NH4+])/([SO42-]+[NO3-]) (abbreviated as R ca), and [ NH4+]/[ Ca2+] (abbreviated as R ac) are useful indices with which to analyze the characteristics of ionic compositions. The annual R sn was 2.54, while this value was around 14.5 at the same site in mid 1980s; 2.77 at Lushan Mountain (Li et al., 2012); 4.4 at Mount Tai (Wang et al., 2008); 4.0 in Shanghai (Huang et al., 2008); and 1.40 at Lulin Mountain (Wai et al., 2008). Further analysis showed that the equivalent ratio of R sn for each sample varied from 0.88 to 5.6, with 72% below 3, and a median of 2.23, indicating that the acidity of rainwater at Huangshan Mountain comes from both nitric and sulfuric acids, with SO42- as the predominant acidic anion. This suggests that rain at Huangshan Mountain is impacted by human activity, e.g., increasing NOx. The R ca can be used as an index for evaluating the degree of anthropogenic activity (Tang et al., 2005). It was 1.67 for all samples, a little lower than that in the mid 1980s (2.07) (Huang et al., 1993), suggesting an increased impact of anthropogenic activities, but still higher than those in neighboring mountains, e.g., 1.25 at Lushan Mountain (Li et al., 2012), and urban areas, e.g., 1.3 in Shanghai (Huang et al., 2008) and 0.73 in Beijing (Tang et al., 2005). R ac reflects the neutralizing capability of the two major cations. The VWM value for all samples was 0.50. In the mid 1980s, this ratio was 1.38 (Huang et al., 1993). Since the 1980s, both NH4+ and Ca2+ have increased, but Ca2+ increased more. This value was 0.63 at Lushan Mountain (Li et al., 2012) and 0.4 in Shanghai (Huang et al., 2008), while it was much higher at Lulin Mountain (3.5) (Wai et al., 2008). Ca2+ comes mainly from wind-borne soil, dust and sand, while NH4+ comes mainly from biological decay, as well as the utilization of fertilizer containing ammonium. The results indicated the presence of dust in East China, reaching heights of over 1800 m.

    Calculation of the inter-correlation between measured ions is a simple way to investigate the possible sources of ions and associations between ions in precipitation. The correlation matrix for the ion pairs is given in Table 2. For the 106 retained samples, the anthropogenic pollutants (SO42-, NO3- and NH4+) and the dust species (Ca2+ and Mg2+) were highly inter-correlated (r>0.6). This suggested those species had common sources or transport mechanisms (Winiwarter et al., 1998). SO42- and NO3- were well correlated because of the same transport mechanisms of their precursors (SO2 and NOx). At present, high NOx emission areas in China are almost superposed with high SO2 emission areas (Li et al., 2012). Ca2+ and Mg2+ were well correlated because of their common dust source. The strong positive correlations between NH4+ and SO42-, NH4+ and NO3-, Mg2+ and NO3-, Mg2+ and SO42-, Ca2+ and SO42-, and Ca2+ and NO3- reflected the reactions between alkaline compounds with acids (HNO3 and H2SO4), suggesting the coexistence of (NH4)2SO4, NH4NO3, CaSO4 etc.

    The correlation coefficients between NH4+ and SO42-, and NH4+ and NO3-, were much higher than those of Ca2+ and SO42-, and Ca2+ and NO3-, indicating the predominance of ammonium sulfate and ammonium nitrate. Similar results were observed at Lulin Mountain in Taiwan (Wai et al., 2008). The correlation coefficient between K+ and NH4+ was much lower than the others (insignificant at 95% confidence level), suggesting that K+ ions were not only from biomass burning. However, we noticed that K+ was highly correlated with Cl- (r=0.89), although it was much lower than Cl-, except for five samples with K+ concentrations comparable with Cl-. This suggests that the two ions might have the same sources, e.g. fertilizer, garbage incineration, and so on.

    To assess the possible sources of rainwater contamination, factor analysis of Varimax rotation was further carried out using SPSS v13.0. Table 3 shows that three factors were identified, and the loadings that exceeded 0.5 are highlighted. The three factors accounted for 88% of total variance. Factor I, accounting for 56% of the variance, best represented a mixture of anthropogenic species (SO42-, NO3-), natural decomposition species (NH4+), and sea/dust species (Na+, Ca2+, Mg2+); strong positive correlations among these ions were found in the correlation analysis (Table 2). Factor II had high loadings for K+ and Cl-, accounting for 20% of the total variance. This factor was mainly associated with anthropogenic sources, e.g., biomass burning and fertilizer use, rather than sea salt, considering the low correlation between Cl- and Na+. Accounting for 12% of the variance, Factor III was best associated with the nature of acidity. Although H+ was correlated with SO42- or NO3- at a statistically significant level (Table 2), it was not loaded in Factor I. The loadings in Factor III indicate that the acidity at Huangshan Mountain was more dominated by SO42- (factor loading of 0.66) and NH4+ (0.56) than by Ca2+ and NO3-, which is different from the results in Shanghai (Huang et al., 2008).

  • The rainfall at Huangshan Mountain shows pronounced seasonal variation (Table 1; Fig. 2a). Thus, monthly and seasonal VWM species concentrations were calculated (Table 1; Figs. 2b and c). From Fig. 2a, it can be seen that the monthly VWM pH does not show a positive correlation with the monthly rainfall.

    Figure 2.  Monthly variations of (a) rainfall amount (mm) and VWM pH value; (b) VWM cation concentrations; and (c) VWM anions concentrations at Huangshan Mountain from July 2010 to June 2011.

    Figure 3 shows the variation of total equivalent concentrations of TC and TA for each sample in units of μeq L-1. It can be seen that the data show striking day-to-day and seasonal fluctuations, reflecting changes in transport direction, an inhomogeneous distribution of sources, differences of ionic sources, and impacts of rainfall. The ratio of TA to TC ranged from 0.83 (winter) to 1.25 (summer) for seasonal average VWM, and 1.13 for the all-samples average VWM. TC exceeded TA in winter and spring, but this ratio was reversed in autumn and summer, reflecting the impacts of monsoon climate. The trajectories from the northwest or north mainly occurred in winter and spring. The northern air masses were usually affected by sand and dust transport and contained more basic ions (e.g., Ca2+). The results of the trajectory analysis could explain this. Figures 2b and c present the monthly VWM concentrations for major ions during the observations. Both anions and cations showed obvious monthly variations, with the higher values from later autumn (November) to early spring (April), and lower in summer, with the highest in November followed by April. The monthly trend of ionic concentrations might be related to the seasonal distribution of airmass sources (see the back-trajectory analysis below), the rainfall, and seasonal agricultural activities surrounding Huangshan Mountain. The concentrations of major alkaline ions (Ca2+ and NH4+) were high in winter and low in summer, consistent with the variation of TC. The concentrations of other cations were very low, except Na+ in January and K+ in April, which might have been due to the impacts of different transport patterns and agricultural activities, e.g., straw burning and fertilizer use. As for anions, the concentration of SO42- and NO3- showed the same trends, i.e., highest in November, followed by April, and lower from June to October. Comparing Figs. 2b and c with Fig. 2a, it can be seen that the monthly VWM concentrations of TA and TC showed obvious negative correlations with the monthly rainfall, although the monthly VWM pH did not show such a correlation. The marked increase or decrease of TA and TC from month to month during the cold season was mainly due to the decrease or increase of rainfall.

    Figure 3.  Variations of total cations (TC) and total anions (TA) in equitable concentration during the observations.

    The seasonal variations of ionic concentrations are shown in Table 1. Almost all ions, except H+, had their highest concentrations in spring/winter and their lowest concentrations in summer, which was different from that of Lushan Mountain (second high in autumn) (Li et al., 2012) and Lulin Mountain (lowest in Autumn) (Wai et al., 2008), but the same as the trends of secondary species in Shanghai (Huang et al., 2008). All these ions showed their lowest concentrations in summer, which was due to the largest rainfall being in this season, as well as the air masses coming mainly from the south and southeast containing relatively low levels of pollutants (see Fig. 4 and Fig. 5). According to the highest seasonal concentration, the ions could be divided into three groups. The first group, including H+, Na+, Ca2+ and NO3-, showed their highest concentrations in winter; while the second group, including K+, NH4+ and SO42-, showed their highest concentrations in spring. For the first group, the feature could have been due to the least rainfall being in winter. In addition, the low temperature in winter would favor the shift of HNO3 in the gas phase to NO3- in the particulate phase (Baez et al., 1997). For the second group, the highest concentrations of K+ and NH4+ in spring could have been due to active agricultural activities, such as fertilizer use and straw burning, taking place in late spring. SO42- in rain is mainly a consequence of the homogenous/heterogeneous oxidation of SO2 followed by dissolution into raindrops by nucleation or washout. Although SO2 usually shows its highest concentrations in winter in urban areas (Huang et al., 2008), sulfate lacked wintertime elevated concentrations: the low temperatures in winter inhibited the conversion of SO2 to SO42-. In addition, the low mixing heights in winter would have inhibited the transport of SO2 from lower elevation source areas to this high-altitude site. The highest SO42- concentration in spring was also observed in Shanghai (Huang et al., 2008). The third group only included Mg2+. Its seasonal VWM concentrations were very close in winter and spring.

    Figure 4.  Horizontal distribution of the cluster-mean 72-h back trajectories to Huangshan Mountain on rain days from July 2010 to June 2011. In each set of parentheses, the initial number is the cluster sequence, and the percentage indicates the ratio of rainfall to the total rainfall amount.

    Figure 5.  Monthly distributions of rainfall amounts of the six trajectory clusters during July 2010-June 2011.

  • Rainwater chemistries from other alpine sites in different locations around the world are compared in Table 5. It should be noted that some measurements were conducted more than 10 years ago, and others were conducted only for several months, so the chemical compositions in rainwater may already have changed, as shown at Lushan Mountain, and the VWM concentrations for some sites may be less representative. However, these data can still present some useful reference information.

    Compared with the measurements at other alpine sites in China, the precipitation pH at Huangshan Mountain was much lower than those measured in Northwestern China, and a little lower than that measured in Taiwan. However, it was higher than those measured in other areas, including Southwestern, Northeastern, central and Southeastern China. The concentrations of anthropogenic species (SO42-, NO3- and NH4+) were much lower than those measured at other continental alpine sites within the latest 10 years, especially for SO42-. In the mid 1980s, Huangshan Mountain showed the lowest concentrations for most species among the continental alpine sites, except for Jade Dragon Snow Mountain. Compared with the mid 1980s, the new measurements at Huangshan Mountain show greatly increased NO3- and Ca2+ concentrations, more than double the SO42- concentrations, and moderate increases in NH4+ concentrations. According to satellite measurements, the tropospheric NO2 column content in East China has increased quickly since 1996 (Richter et al., 2005). Meanwhile, national SO2 emissions have changed little since the beginning of the 1990s (Wang and Xu, 2009). Therefore, the changes in NOx and SO2 emissions are clearly reflected by the change of the chemical composition of rainwater, e.g., here, and those at Lushan Mountain. The highest of the Ca2+ concentrations were in northwestern China (Tianshan Mountains), the second highest in central China (Lushan Mountains), followed by Northeastern China (Mount Tai). The Ca2+ concentrations at Huangshan Mountains were in the middle, higher than those in Southwestern and Southeastern China. As a biomass burning tracer, K+ concentrations showed different spatial trends than Ca2+ and the anthropogenic species, with the highest at Lushan Mountain, second highest at Mount Tai, followed by Huangshan Mountain. The mountains with the three highest K+ concentrations were all located in agricultural areas. Therefore, the spatial distribution of K+ concentrations reveal the impacts of biomass burning and fertilizer use on rain chemistry. Na+ concentrations were highest at Tianshan Mountains, second highest at Mount Tai, and lowest at Jade Dragon Snow Mountain. Mg2+ concentrations were highest in northwestern China and lowest at the southwestern site (Mount Emei). The concentrations of Na+ and Mg2+ at Huangshan Mountain ranked in the lower level among the continental alpine sites in China.

    Although most ionic concentrations in the rain at Huangshan Mountain were much lower than other contemporary measurements in mainland China, the precipitation pollution was much more serious than those at Lulin Mountain (island site) (Wai et al., 2008), Whiteface Mountain (USA) (Aleksic et al., 2009), Lougheed Provincial Park (Canada) (Lafrenière and Sinclair, 2011) and Mount Fuji (Japan) (Watanabe et al., 2006). Compared with the measurements at the above four mountain sites, the precipitation pH at Huangshan Mountain was lower than that of Lulin Mountain only; however, it had the highest concentrations of almost all species, especially the anthropogenic ions and Ca2+.

    In summary, the precipitation at Huangshan Mountain is less polluted than at other high-altitude mountains in mainland China, probably because of its higher altitude, the greater geographical extent of its mountain range, and its distance from urban areas. However, compared with the 1980s, almost all ionic concentrations have increased greatly, and pH has decreased from near-neutral to acidic.

4. Impacts of transport patterns on ionic concentrations in precipitation
  • Figure 4 shows the distributions of the horizontal components of the six cluster-mean back trajectories. The monthly distribution of rainfall in each trajectory group is shown in Fig. 5. It can be seen that cluster 1 contributed the highest percentage of rainfall, with 21.7% of total trajectories and an average rainfall of 35.7 mm for each rain event. In this cluster, the rainfall mainly occurred in June and July, belonging to the typical mei-yu rain (summer monsoon) season. Cluster 2 had the second highest percentage of rainfall, with the highest percentage (35.8%) of total trajectories and an average rainfall of 17.6 mm. The rain events in this cluster occurred in almost all months except February, while most of the rain fell in June to October. Cluster 3 had the third highest percentage of rainfall but the fewest rain events (5.7%) with the highest average rainfall (48.9 mm). The rain events in this cluster mainly occurred in June, also within the mei-yu season. Cluster 4 contributed 12% of the total rainfall, with 12.3% of total trajectories and the average rainfall per event ranked third (22.3 mm) among the six clusters. The rainfall in this cluster mostly occurred from June to September. Cluster 5 contributed 10.7% of the total rainfall with 17% of trajectories, with low average rainfall (14.4 mm). Its rain events occurred in all months except July and November. Originating in Mongolia, cluster 6 was composed of the longest trajectories. It had the lowest percentages of both rainfall and trajectories and the lowest average rainfall (10.1 mm). Its rain fell in all seasons except summer.

  • Table 4 presents the VWM ionic concentrations for each of the six clusters. It can be seen that the cluster-mean pH varied from 4.54 (cluster 6) to 5.69 (cluster 3). The cluster-mean K-value varied from 10.8 (cluster 4) to 20.6 (cluster 6) μS cm-1. The pH values of clusters 3, 4 and 5 were higher than those of the other three, while their K-values were lower. Both the lowest mean pH and the highest mean conductivity appeared in cluster 6, followed by cluster 2 and cluster 1 with increasing pH and decreasing conductivity. The rain in cluster 3 had the highest pH and low conductivity.

    As far as rainwater pollution was concerned, rain in cluster 6 was the most polluted; however, it contributed only 3.3% to the total rainfall, so its impacts were limited. Apart from K+, most ionic concentrations in rain of this cluster were the highest among the six. This could have been due to the lowest average rainfall per sample and to the traversal of this cluster through high-emission areas. The trajectories in this cluster originated in Mongolia, and traversed over a high-emission source area of SO2 and NO2. Therefore, the lowest R sn appeared in this cluster. The rain in cluster 3 was the cleanest. Trajectories of cluster 3 originated from the South China Sea with the highest average rainfall and came through areas of low NO2 and low SO2 emissions (Li et al., 2012, Fig. 11). Therefore, rain in cluster 3 had the lowest concentration for all ions and the highest R sn.

    Composed of trajectories originating from the ocean area south of Hainan Island, the rain in cluster 1 had relatively low concentrations for all ions except Ca2+, with the second highest R sn, the highest R ca and the lowest R ac. Since the trajectories in this cluster originated over the ocean, occurred mainly in summer, and traversed Guangdong, Jiangxi, Hunan and Hubei provinces, it is difficult to understand the high concentration of Ca2+ in the rain. However, the high concentration of Ca2+, together with relatively low concentrations of other ions, was also observed in the rain of similar trajectories at Lushan Mountain [cluster 1 in (Li et al., 2012)]. Therefore, there might be some high Ca2+ emission industries along the pathway, or there exists some other transport mechanism that could not be detected by the 72-h trajectories. Anyway, this cluster seemed less polluted, except for Ca2+. Cluster 2 was composed of trajectories revolving around Huangshan Moutain with the shortest cluster-mean trajectory, mainly originating from Jiangxi, Anhui, Zhejiang and Jiangsu provinces. With relatively low average rainfall per sample by slow-moving air masses, the ionic concentrations in the rain of cluster 2 were relatively high among the six, e.g., the highest SO42- and K+, and the second highest NH4+ and NO3-, showing the impacts of anthropogenic sources and the activities of biomass burning. Thus, the emissions of Jiangxi, Anhui, Zhejiang and Jiangsu provinces had the major impact on rain chemistry at Huangshan Mountain. Cluster 4 was similar to cluster 3 in many aspects. Both mainly occurred in summer, originated in the ocean, and traveled most over the ocean. However, cluster 4 traveled over the Yangtze Delta while cluster 3 traveled over less developed areas, which led to higher concentrations of anthropogenic pollutants in rain of cluster 4. Cluster 5 was similar to cluster 4 because both clusters traveled over the areas well developed with high emissions of SO2 and NOx in East China and partly over the ocean. The differences were the area of origin, the incoming direction, and the season of occurrence. Cluster 5 originated in Inner Mongolia and passed through North China and the Bo Sea. Thus, the rain in cluster 5 had higher concentrations of SO42- and Ca2+, and a lower R ac and higher R ca than those in cluster 4; while the concentrations of NH4+ and NO3- were very close in the two clusters.

    (Li et al., 2012) performed a similar back-trajectory cluster analysis for rain at Lushan Mountain and also obtained six clusters. Fortunately, we had some clusters with similar places of origin and transport directions, e.g., cluster 1 at both sites, and cluster 3 at Huangshan Mountain and cluster 5 at Lushan Mountain. Comparing the results at Huangshan Mountain with those at Lushan Mountain [also included in Table 4, as well as Table 5 in (Li et al., 2012)], although there were large differences between the ionic concentrations of the corresponding clusters at the two stations, the corresponding values of R sn,R ac and R ca were very close. This indicates that our analyses of precipitation chemistry at Huangshan Mountain are reliable.

    To summarize, the precipitation in cluster 6 was the most polluted, followed by cluster 2; precipitation in cluster 3 was the least polluted; while precipitation in cluster 1 was less polluted than that of cluster 5 and more polluted than that of cluster 4.

5. Conclusions
  • The first year-round analyses of major ion concentrations in rainwater from Huangshan Mountain have been reported in this paper, as well as a comparison with other alpine sites and the impacts of transport patterns on ionic concentrations. The main findings can be summarized as follows:

    (1) The VWM pH value of the rainwater at Huangshan Mountain was 5.03 for the period from July 2010 to June 2011, a little lower than that of typical natural water (5.6).

    (2) In the rainwater samples at Huangshan Mountain, SO42- and Ca2+ were the most abundant anion and cation, respectively. The ionic concentrations were highest in winter/spring and lowest in summer.

    (3) Most ion concentrations were highly inter-correlated, suggesting the alpine precipitation events were fully mixed and had common sources for some species. The value of R sn (2.54) indicated that the acidity of rainwater at Huangshan Mountain comes from both nitric and sulfuric acids, with SO42- being the predominant acidic anion.

    (4) Compared with the measurements at other high mountain sites in China in the lastest 10 years, the rainwater at Huangshan Mountain was the least polluted, i.e., it had the lowest ionic concentrations, the lowest conductivity, and the highest pH.

    (5) All rainfall events during the sampling period were classified into six groups according to their airmass 72-h back trajectories. The corresponding cluster-mean pH, K-values and ionic compositions were different for each cluster, showing significant impacts of seasonal rainfall and regional transport. The rainwater with influencing air masses originating in Mongolia was the most polluted with limited impacts. The emissions of Jiangxi, Anhui, Jiangsu and Zhejiang provinces had a strong influence on the overall precipitation chemistry at Huangshan Mountain due to its high rainfall percentage. The rainwater that traversed over North China was heavily polluted by anthropogenic pollutants.

Reference

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