Environ Sci Pollut Res DOI 10.1007/s11356-014-3583-3
RESEARCH ARTICLE
Spatial distribution and source apportionment of atmospheric dust fall at Beijing during spring of 2008–2009 Rende Wang & Xueyong Zou & Hong Cheng & Xiaoxu Wu & Chunlai Zhang & Liqiang Kang
Received: 22 May 2014 / Accepted: 8 September 2014 # Springer-Verlag Berlin Heidelberg 2014
Abstract Beijing is a megacity, where atmospheric dust fall amount is great, and its resultant air pollution is serious. So, analyzing the chemical elements in atmospheric dust fall and revealing its various sources can provide a scientific basis for taking effective measures to improve atmospheric environmental quality. In this paper, we investigated the spatial and temporal distribution of dust fall in Beijing, based on the dust samples collected in the spring of 2008 and 2009 at 18 observation sites laid out in Beijing and then analyzed the sources of atmospheric dust fall based on the test of samples, adopting enrichment factor and factor analysis methods. Our results found that the dust fall quantity in the observation periods was respectively 33.6230 t km−2 and 28.7130 t km−2; the dust fall quantity varied significantly in different months in the spring, but the variation trend was similar at the sites. There were two centers of large quantity in Beijing; one was in the southwest of downtown, and the other was in the northeast of downtown. The spatial distribution of dust fall generally showed a structural feature of three loops; the northwestern mountainous area was a small quantity belt; the plain area around the downtown was a large quantity belt, and the central downtown was a center of small quantity. Soil dust, construction dust, coal dust, and vehicle exhaust were Responsible editor: Constantini Samara R. Wang : X. Zou (*) : H. Cheng : X. Wu : C. Zhang : L. Kang State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Xinjiekouwai Street No.19, Beijing 100875, China e-mail: [email protected] R. Wang Institute of Geographical Sciences, Hebei Academy of Sciences, Shijiazhaung 050021, China X. Wu College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
the four major sources of dust fall in spring of Beijing, respectively, accounting for 38.50, 22.25, 14.06, and 20.82 % of the total dust fall quantity. Keywords Beijing . Atmospheric dust fall . Spatial distribution . Source apportionment
Introduction In the last three decades, with the rapid growth of China’s economy, acceleration of urbanization, and rapid increase of energy consumption and car ownership, urban air pollution is on the rise (State Environmental Protection Administration 2004). In most Chinese cities, atmospheric particulates are the primary pollutant affecting urban air quality (State Environmental Protection Administration 2000). Beijing, as a megacity with the population of over 18 million, is also facing serious atmospheric particulate pollution (Chan et al. 2005). Especially in the spring, not only do motor vehicles, construction sites and roads, catering industry, coal heating and industrial plants discharge large amounts of particulate pollutants, but also strong monsoon brings a lot of dust from inside and outside of Beijing (Zhuang et al. 2001; Dong et al. 2007), so the atmospheric particulates in Beijing have many emission sources, leading to atmospheric particulate pollution and threat to residents’ health (Zhao et al. 2006). Atmospheric dust fall is one of the important indices for urban atmospheric environment monitoring, and it can reflect the seriousness of atmospheric particulate pollution (Guo et al. 2006). Analysis of the physical and chemical characteristics of urban atmospheric dust fall and the sources of particulates have important reference values in control of urban atmospheric particulate pollution (Guo 2008; Tian et al. 2011). Researches on atmospheric dust fall in Beijing were carried out earlier (Chen et al. 1989) and especially the several strong
Environ Sci Pollut Res
dust storms occurring in the spring of 2,000, making the researches increasingly focused on. By analyzing the physical and chemical characteristics of atmospheric dust fall caused by a single dust storm, researchers could discriminate the sources of particulates and their effects on environment (Zhang et al. 2000; Gao et al. 2002a, b; Guo et al. 2004). In recent years, with the rapid increase of car ownership and urban construction expansion, studies on automobile emissions and dust reentrainment on construction sites and roads have attracted more and more attention (Han et al. 2007; Fan et al. 2009). Overall, existing studies are mostly based on the results of a singular sampling site and lack a comprehensive understanding of the dust fall characteristics in the entire region of Beijing, as well as dust source apportionment. In fact, Beijing, a megacity located in northern China, often suffers from the invasion of strong wind, bringing dust and sand in spring, and dust pollution occupies a large proportion of moderate and severe pollution. By source apportionment of atmospheric dust, we not only can learn about the impact of manmade pollution sources on atmospheric environment, but also about the harm to atmospheric environment caused by dust storms, which is a essential supplement to studies on fine particulate matters (PM10 and PM2.5) (Song et al. 2006a; b). Based on the reasons above, we investigated the characteristics and the sources of atmospheric dust fall from March to May in 2008 and 2009.
Methods Collection of dust samples Totally 18 sampling sites were arranged in Beijing (Fig. 1), among which six sampling sites, namely Haidian, Men toug ou, Chao yan g, Tongz hou , Fen gtai, a nd Guanxiangtai, were located in the urban area or suburban plain area; six sampling sites, namely Changping, Shunyi, Huairou, Pinggu, Daxing, and Fangshan, were located in the outer suburban plain area; two sampling sites, namely Yanqing and Miyun, were located in the transition area of outer suburban plain and mountains; and four sampling sites, namely Yanqing Foyeding, Huairou Tanghekou, Miyun Shangdianzi, and Zhaitang, were located in the outer suburban mountains area. Sampling devices were installed in standard meteorological observation stations affiliated with The Beijing Meteorological Bureau; the ground of the observation fields was artificial grass and not shielded by surrounding buildings and trees, and the surrounding environment of the sampling sites was same. Each sampling site was installed with two sets of dust collecting devices with the distance of 2 m. The dust collecting device was mainly composed of dust collecting glass cylinder and steel bracket. The glass cylinder was
60 cm in height and 30 cm in diameter and fixed on a bracket 0.9 m above the ground, and the glass cylinder port was 1.5 m above the ground, equivalent to the height of mouth and nose of ordinary people (Fig. 2). The sampling time was from March to May in 2008 and 2009. The sampling frequency of the two sets of devices at each sampling site was different. One set collected samples at 17:00 every 10 days and the other collected samples, at 17:00 at the end of every month. In this paper, we analyzed the dust collected monthly in the spring of 2008 and 2009. No material was added into glass cylinders, and we rinsed the inner wall of the cylinder with distilled water when sampling, poured the turbid liquid into a clean wild-mouth bottle, and repeated several times, until the inner wall and bottom of the cylinder were rinsed clean. After sampling, we covered the bottle with a cap, filled in the label, and placed it in a dry and cool place for later handling. Sample handling and testing We poured the turbid liquid of the collected dust sample into a beaker, placed it in an oven, and dried it constant at 60 °C; we used a brush to clean out the dust sample in the beaker, placed it into a plastic sample bag that was weighed and labelled, weighed it with a 1/1,000 electronic balance again, and calculated the net weight of each sample collected. We used an ULTIMA inductively coupled plasma spectrometer (ICP-MS) produced by French JY Company to analyze the contents of 17 elements, namely Al, As, Ba, Ca, Co, Cr, Cu, Fe, Mg, Mn, Ni, P, Pb, Ti, V, Zn, and S, in the dust samples, with the analytical precision of 0.01 μg g−1. The test was made in the Analysis and Testing Center in Beijing Normal University. Figure 3 shows the experiment procedure in detail. We used the same method to measure the contents of the elements in the blank sample and obtained the true contents of the elements in the sample by the measured contents of the elements minus the contents in the blank sample. Dust source apportionment In this study, enrichment factor method and factor analysis method were adopted to analyze the sources of dust particulates. Enrichment factor method Enrichment factor method is to compare the contents of elements in dust particulates and known particulates, analyze the degree of enrichment of elements in particulates, and determine whether particulates are from known substances; it is a qualitative method in source apportionment (Reimann and Caritat 2000). This method is generally combined with quantitative analytical methods to make mutual authentication. The
Environ Sci Pollut Res
Fig. 1 Distribution of dust fall sampling sites
formula is: ðCi=C R dustfall Ef ¼ 0. Ci background 0
ð1Þ
CR
Where Ci and CR are contents of element i and R in dust fall; C′i and C′R are contents of element i and R in soil (Table 1). R is a reference element, and in this paper, Al was selected as the reference element. When Ef≤1, it is considered that an element is from the natural source, for the reference element Ef=1; when 110, it is considered that an element is from the artificial source (Loska et al. 1997).
Factor analysis method Factor analysis method can not only qualitatively identify the sources of atmospheric particulates, but also quantitatively calculate the contribution of each source to the total particulate pollutants, and it is an analysis method commonly used in dust fall source apportionment (Sun et al. 2008). Principle of factor analysis method is to attribute some variables or samples with complex relationships to several comprehensive factors, on the basis of the recognition that certain correlation exists between the variables related with pollution sources and in the condition of no loss of main information (Hopke et al. 1976), and it can be expressed as the following formula: X ji ¼ a j1 F 1i þ a j2 F 2i þ ⋅⋅⋅ þ ajp F pi þ d j U ji
Fig. 2 Dust fall samplers (marked in ovals)
ð2Þ
Where Xji is a linear combination of factor Fji (applicable to all the variables) and unique factor Uji (applicable to each variable), aji is a factor load coefficient to each variable, and dj is a standard regression coefficient to unique variable j. The main purpose of factor analysis is to obtain factor load coefficient aji of common factor. The value of factor load coefficient reflects the degree of correlation between factor and variable. This method is to make calculations with the actually measured contents of elements in dust fall particulates and make analysis by combining the specific situation in
Environ Sci Pollut Res
Step 1: Adding acid Place 0.1g dried dust sample into a digestion tank. Add 5.0ml HNO3. Add 2.0ml HCl and 1.0ml HF.
Step 2: Digestion Digestion at 150 ć for 6 hours.
Step 3: Evaporation Open the lid. Place the sample solution in a ventilated hood. Dry to one drop.
Step 4: Constant volume Add 1.0 ml HClO3. Transfer the solution into a test tube.
Step 5: Dilution Dissolve to the volume of 100ml.
Step 6: Test Directly use the HR-ICP-MS method to measure the contents of the elements.
constant
Fig. 3 The procedure of analyzing the contents of elements using inductively coupled plasma spectrometer (ICP-MS)
Beijing, to obtain the main sources of dust fall substances and their contribution rates.
In 2008, the dust fall quantity in March, April, and May was respectively 6.99, 10.03, and 16.61 t km−2, accounting for respectively 21.79, 29.83, and 49.38 % of the total dust fall quantity in the spring, and the dust fall quantity was largest in May and smallest in March. Among the 18 sampling sites, 17 sites had the same feature of the monthly variation, and only at Haidian site was the dust fall quantity in March larger than that in April. In 2009, the dust fall quantity in March, April, and May was respectively 6.59, 12.73, and 9.38 t km−2, accounting for respectively 22.96, 44.35, and 32.69 % of the total dust fall quantity in the spring, and the dust fall quantity was largest in April and smallest in March. Among the 18 sampling sites, 14 sites had the same feature of the monthly variation; only at Foyeding and Shangdianzi sites in the northern mountain area
Results Features of dust fall Dust fall quantity In 2008, the atmospheric dust fall quantity in the spring of Beijing was 21.74–48.43 tons per square kilometers (t km−2), averagely 33.63 t km−2. In 2009, it was 13.98–39.81 t km−2, averagely 28.71 t km−2 (Fig. 4). Table 1 Average content of elements in topsoil around Beijing city Elements
Al
As
Ba
Ca
Cd
Co
Cr
Cu
Fe
Average content (μg g−1) Standard deviations Elements Average content (μg g−1) Standard deviations
36,733.93 5,286.54 Mg 7,333.67 642.55
19.55 4.25 Mn 741.44 25.36
1,223.22 95.43 Ni 49.43 1.99
1,4076.17 496.81 P 695.65 31.53
1.04 0.19 Pb 39.68 4.32
44.11 3.86 Ti 3951.33 221.67
152.69 3.94 V 127.01 17.43
32.56 1.93 Zn 100.52 34.70
2,5427.65 882.88 S 239.70 21.14
The average of 40 topsoil samples in Beijing
Environ Sci Pollut Res
quantity around the central downtown. The central downtown was the center of small dust fall quantity. The dust fall quantity in the northwestern mountain area was smaller, forming an obvious belt of small dust fall quantity around the northwest of the central downtown. Overall, the spatial distribution of dust fall in Beijing generally showed a structural feature of three loops; the northwestern mountainous area was a small quantity belt, forming the outer loop; Fengtai, Mentougou, Changping, Shunyi, Tongzhou, Daxing, and Fangshan, located in the plain area around the downtown, which was a large quantity belt, forming the middle loop; the inner loop covered most part of the central downtown, which was the center of small quantity (Fig. 5). Relationship between dust fall and dust storm The statistical results showed that the dust fall quantity was significantly larger in years with relatively large number of dust weather days in the spring of 2000–2009 (Fig. 6, Table 2). Dust fall quantity in spring had certain correlation with interannual variations of number of floating dust days and blowing sand-dust days. This indicated that dust weathers, especially blowing sand-dust, have important influence on spring dust fall quantity in Beijing. Atmospheric dust fall and pollution Fig. 4 Spring dust fall amount at different sampling sites in 2008 (a) and 2009 (b)
was the dust fall quantity in March larger than that in May, and at Tongzhou and Miyun sites, the dust fall quantity was largest in May and smallest in March. Spatial distribution of dust fall The spatial distribution of dust fall quantity was quite different. In the spring of 2008, the dust fall quantity was largest in Fengtai (48.43 t km−2) and smallest in Miyun Shangdianzi (21.74 t km−2). In the spring of 2009, the dust fall quantity was largest in Tongzhou (39.81 t km−2) and smallest in Yanqing Foyeding (13.98 t km−2). There were two centers of large dust fall quantity in Beijing (Fig. 5). One was in the southwest of the city, centered by Fengtai, including parts of Fengtai District, Mentougou District, Fangshan District, and Shijingshan District; the other was in the northeast of the city, centered by Shunyi, including parts of Shunyi District, Miyun District, Huairou District, and Tongzhou District. In addition to the two areas with large dust fall quantity, Changping, Daxing, and several other plain areas also had relatively large dust fall quantity and connected with the above-mentioned two areas, forming a belt of large dust fall
The statistical result showed that there was good correlation between dust fall quantity and number of days of moderate and severe atmospheric pollution in the spring of 2000–2009 (Fig. 7), and the indicator of dust fall quantity could generally reflect the atmospheric pollution in spring of Beijing. Further analysis also showed that atmospheric pollution in spring of Beijing was mainly caused by blown sand and dust (Table 2); the number of days of dust pollution accounted for 42.9– 100 % of the number of days of moderate to severe pollution in the spring of 2000–2009, and the correlation coefficient reached 0.814. Dust fall source apportionment Enrichment of elements in dust fall With the contents of elements in topsoil in Beijing as the background values (Table 1) and Al as the reference element, the analysis on the degree of enrichment of various elements in dust by enrichment factor method showed that the elements with the enrichment factor 10 included only S (Fig. 8). The elements with the enrichment factor close to 1 in atmospheric
Environ Sci Pollut Res
Fig. 5 Spatial distribution of spring dust fall amount in 2008 (a) and 2009 (b)
particulates mainly include soil wind erosion products, and if enrichment factor >10, then the element is enriched, mainly from various pollution elements caused by human activities. For elements with the enrichment factor in 1–10, manmade pollution also takes a certain proportion (Manoli et al. 2002). Accordingly, it is considered that Al, Ba, Co, Cr, Fe, Mn, Ni, Ti, and V are not enriched and mainly from the soil in Beijing or in its adjacent regions; S is significantly enriched in atmospheric dust fall due to human activities and mainly manmade pollution sources; As, Ca, Cu, Mg, P, Pb, and Zn are partly from the soil, but human activities have significant effects on enrichment of these elements. Fig. 6 Correlation of spring dust fall and dust days
Dust fall source apportionment Analysis on correlations among 17 elements in dust showed that Al, Ba, Fe, Ti, and V were significantly correlated, with the correlation coefficient above 0.8 and the enrichment factor ≤1, and mainly from soil dust (Chow et al. 2003); As and S were typical identification elements in coal dust; the correlation coefficient was the highest (0.68), and their enrichment factors were significantly greater than 1, mainly from coal combustion discharge (Yatkin et al. 2008); Cu, Zn, and Cr had good correlations; the correlation coefficient was above 0.65, and the enrichment factors of these elements were in 1–10,
Environ Sci Pollut Res Table 2 Dust days, severe pollution days, and spring dust fall amount from 2000 to 2009 Year
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
Dust fall amount in suburban area (t km−2) Blowing sand-dust daysc Floating dust daysc Moderate and severe pollution days (days)d Dust pollution daysd
71.1a 14 8 13 11
66.6 a 11 13 15 12
66.3 a 21 8 11 10
39.9 a 1 0 2 1
43.8 b 6 1 7 3
38.4 b 7 4 8 4
60.3 b 15 9 14 9
42.6 b 4 5 2 2
35.4 9 6 7 6
32.3 3 2 1 1
a
From Guo et al. (2006)
b
From Guo (2008)
c
From China Meteorological Administration (2010)
d
From Beijing Municipal Environmental Protection Bureau (2010)
indicating that they were affected by manmade sources (Table 3). Cu, Zn, and Cr were mainly from combustion, waste incineration, and metal smelting, so they could be regarded as the identification elements of incineration and smelting dust (Watson and Chow 2000); Ca and Mg had relatively high correlation coefficients, and their enrichment factors were significantly greater than 1, among which Ca was mainly from emissions from construction processes and was the main identification element of construction cement dust, and Mg was a common element in soil dust and construction dust (Chow et al. 2004); Pb and Mn had a relatively high correlation coefficient, reaching 0.98, among which Pb was mainly from automobile exhaust and the identification element of automobile exhaust dust (Ho et al. 2003), and these two elements were certainly correlated with Al, Fe, V, and other soil identification elements, indicating that these two elements were partly from soil dust. The other three elements, Co, P, and Ni, had certain correlations with other elements, but the correlation coefficients were not high, indicating that the sources were relatively complex, among which Co might be Fig. 7 Correlation of spring dust fall and pollution days
from soil dust and fuel, P might be from coal dust and metallurgical dust, and Ni might be from soil dust and coal dust (Watson and Chow 2000). Accordingly, eight elements, Al, Ti, Ca, Cu, Pb, Mg, Fe, and As, selected from the measured 17 elements, were regarded as the identification elements of various sources. The identification elements of various emission sources were respectively Al, Ti, and Fe for soil dust; As for coal dust; Ca and Mg for construction cement dust; Pb for automobile exhaust dust; and Cu for incineration and smelting dust. Factor analysis function in Statistical Product and Service Solutions (SPSS 11.5) was used to make source apportionment of dust collected respectively in urban and suburban areas. For areas with clean atmosphere, initial load factor matrix is generally selected; for areas with polluted atmosphere, rotated load matrix should be selected (Song et al. 2006b). Atmospheric pollution was relatively serious in spring of Beijing, so the initial factor load matrix should be made using Varimax rotation in order to obtain the rotated factor matrix. Then the rotated factor matrix was made
Environ Sci Pollut Res
Fig. 8 Enriching factor of element in spring dust fall in March (a), April (b), and May (c) of 2008 and in March (d), April (e), and May (f) of 2009
regularization reduction to obtain the ultimate factor load matrix of dust in each month, and by analysis and interpretation, the main sources of dust and their contribution rates were determined. The final results showed that soil dust, construction dust, coal dust, and automobile exhaust were four major sources of dust in spring of Beijing, accumulatively accounting for more than 90 % of the total dust sources (Table 4). Among which, soil dust from farmland by wind erosion was
the leading source of dust fall, accounting for 26.88–50.23 % of the dust fall quantity in each month and was the primary source in most months. Construction dust occupied a certain proportion in each month and was even the primary source in some months. Automobile exhaust dust occupied a relatively large proportion in urban area and was even the primary source in some months; it occupied a relatively small proportion in suburban areas and was even not a main component of
Environ Sci Pollut Res Table 3 Correlation matrix of different elements
Al As Ba Co Cr Cu Fe Mg Mn Ni P Pb Ti V Zn Ca S
Al
As
Ba
Co
Cr
Cu
Fe
Mg
Mn
Ni
P
1.00 −0.51 0.81 0.61 0.29 0.41 0.99 0.17 0.58 0.55 −0.52 0.69 0.86 0.98 0.31 −0.46 −0.51
1.00 −0.02 −0.56 0.38 0.14 −0.57 −0.82 −0.48 0.29 0.38 −0.50 −0.51 −0.38 0.09 −0.45 0.68
1.00 0.55 0.47 0.55 0.78 −0.19 0.19 0.84 −0.35 0.28 0.70 0.85 0.27 −0.80 −0.25
1.00 0.02 0.58 0.57 0.27 0.17 0.08 0.09 0.17 0.49 0.53 0.19 0.00 −0.06
1.00 0.67 0.25 −0.35 −0.29 0.62 0.10 −0.12 0.46 0.45 0.88 −0.72 0.05
1.00 0.30 −0.45 0.00 0.28 0.50 0.05 0.29 0.47 0.77 −0.38 0.45
1.00 0.27 0.56 0.55 −0.62 0.68 0.90 0.97 0.25 −0.44 −0.62
1.00 −0.02 −0.22 −0.48 0.04 0.44 0.08 −0.22 0.70
1.00 −0.10 −0.32 0.98 0.20 0.49 −0.08 0.14
1.00 −0.51 0.04 0.63 0.66 0.24 −0.98
1.00 −0.42 −0.62 −0.51 0.31 0.35
−0.74
−0.18
−0.38
0.53
dust fall in some months, which was related with more vehicles in urban area and less vehicles in suburban areas. In most months, the content of coal dust in suburban areas was higher than that in urban areas, which was related with more industrial enterprises and residential heating using a lot of coal in suburban areas. Dust fall in most months, especially in urban areas, did not contain dust produced by waste incineration and metal smelting, which benefited from elimination of a large number of polluting enterprises, coal dust, and vehicle exhaust.
Pb
Ti
V
Zn
Ca
1.00 0.38 0.63 0.06 0.01
1.00 0.89 0.41 −0.51
1.00 0.42 −0.59
1.00 −0.35
1.00
−0.31
−0.73
−0.49
0.16
0.20
S
1.00
Discussions Dust fall quantity in the spring of 2008 was significantly larger than that in 2009, about 1.1 times of that in 2009, which might be related with more days of dust storm in the spring of 2008 than in 2009. According to the meteorological data (Table 2), totally 15 times of dust storm occurred in Beijing in the spring of 2008 and only five times in 2009, and dust storm brought a large quantity of particulates. The results of dust source apportionment also showed that the content of soil dust in the
Table 4 Contribution to spring dust fall from main sources in 2008 and 2009 Time (year, month)
2008, 03 2008, 04 2008, 05
Region
Soil dust
Construction dust
Coal dust
Vehicle exhaust
Incineration and smelting dust
Total
Urban Suburban Urban Suburban Urban Suburban
40.24 32.93 50.23 50.21 43.53 35.45 42.10
27.74 36.86 13.41 14.68 13.38 18.12 20.70
13.40 15.97 16.29 22.88 13.48 8.54 15.09
14.63 13.53 18.80 12.23 29.09 21.78 18.34
– – – – – 16.11 2.69
96.01 99.29 98.73 100.00 99.48 100.00 98.92
Urban Suburban Urban Suburban Urban Suburban
34.09 47.65 33.48 34.25 33.06 26.88 34.90
24.07 25.41 28.76 29.13 15.80 19.60 23.80
16.63 14.08 – 13.35 – 34.12 13.03
23.50 12.65 22.68 16.48 46.69 17.78 23.30
– – 14.24 – – – 2.37
98.29 99.79 99.16 93.21 95.55 98.38 97.40
Average 2009, 03 2009, 04 2009, 05 Average
Contribution ratio (%)
Environ Sci Pollut Res
spring of 2008 was significantly higher than that in 2009 (Table 4), indicating that dust storm frequency and intensity are important factors affecting atmospheric dust fall quantity in spring of Beijing. The dust fall quantity was quite different at each observation site in different months, but the trend of inter-monthly variation of dust fall quantity in spring is almost similar. In 2008, among the 18 observation sites, 17 sites showed the largest dust fall quantity in May, followed by April, and smallest in March; in 2009, among the 18 sites, 14 sites showed the largest dust fall quantity in April, followed by May, and smallest in March, indicating that dust fall intensity in various areas in Beijing was affected by common factors. Coal dust, automobile exhaust dust, and construction dust were local dust sources, had relatively small range of influence, and would not extensively affect the dust fall quantity in Beijing, so the frequencies of strong winds and dust storms in different months might be the main cause affecting the intermonthly variation of dust fall quantity in spring. The different trend of variation of dust fall quantity at few sites might be affected by local dust sources or caused by human factors. The dust fall quantity is always relatively large in the southwest and northeast of Beijing, and they are the centers of large dust fall quantity, which might be related with nearsurface atmospheric circulation and the coupling effects of underlying surface. The analysis on near-surface airflow field shows that northwest wind is prevalent from March to May every year in Beijing, and the wind enters the southeast plain area after crossing the low ridges in Badaling and Qingshuiding and jointly affected by wind field divergence and mountain obstruction, forms a closed circulation respectively in the northeast and the southwest, with the middle air passage as the boundary. The northeast circulation is centered by Shunyi, covering the mountain front areas in Shunyi, Pinggu, Huairou, Miyun, and several other districts. The southwest circulation is centered by Fengtai, covering the mountain front areas in Fengtai, Fangshan, Shijingshan, Mentougou, and several other districts (Zhao et al. 2006). In the circulations, air activity is weak and easy to form downdraft, which is conducive to settling of particulates. In addition, Fengtai and Mentougou are centralized industrial regions in Beijing, and large quantity of particulate pollutants emitted from industrial production is bound to increase dust fall. The northeast is distributed with large areas of farmland, and soil wind erosion provides a large amount of material bases for dust fall. Small dust fall quantity in the northwestern mountainous area is due to large vegetation coverage, limited surface dust quantity, and long distance to urban area; it is less affected by manmade pollution sources, and dust fall is mainly from the longdistance transportation by upwind from outside of Beijing (Zhuang et al. 2001). The dust fall quantity in the urban areas is relatively small (Fig. 5), which might be related with hard ground and lack of soil dust sources in the urban areas.
In the four major sources of dust fall, soil dust takes the largest share. According to different sources, soil dust can be divided into outside soil dust and inside soil dust. Outside soil dust is carried by wind from outside of Beijing, and its affecting range is very big, but regional difference is small. Inside soil dust is mainly from bare farmland around Beijing (Chen et al. 2003), and its main affecting range is mainly in the surrounding area of farmland. Currently, there is still some controversy on the issue of contribution of inside and outside dust sources to the dust fall in Beijing (Li and Gao 2001; Gao et al. 2002a, b). Existing study results show that floating dust and dust storm particulates are mainly from outside, and blown dust particulates are mainly from inside sources (Ye et al. 2000; Yang et al. 2002). Among the days of dust weather in Beijing in recently 50 years, floating dust and dust storm account for respectively 20 and 9 %, and the remaining 71 % is blowing sand (Chen 2001). It can be seen that the local soil dust in Beijing is also an important source of atmospheric dust particulates. For reducing atmospheric particulate pollutants, in addition to continuing to strengthen the comprehensive control of the ecological environment of outside dust sources, we must also do well in control of local dust sources in Beijing. Construction dust is the second largest source of dust fall in Beijing, and it is mainly produced in illegal discharges during construction. In recent years, most construction projects in Beijing are in the suburbs, and the percentage content of construction dust in suburban areas is significantly higher than that in the central downtown. Automobile exhaust dust occupies a relatively large proportion of dust fall in urban area and a relatively small proportion in the suburban areas, which is directly related with higher density of vehicles in the urban areas and lower density in suburban areas. In most months, the content of coal dust in suburban areas is higher than that in urban areas, which is related with more industrial enterprises and larger coal consumption for residential heating in suburban areas.
Conclusions The dust fall quantity in Beijing in the spring of 2008 was significantly larger than that in 2009, due to more days of dust storm in the spring of 2008 than in 2009. The dust fall quantity varied in different months in spring, but its variation trend is similar, because the dust fall intensity in various regions of Beijing is affected by wide-range wind fields. The central downtown is the center of small dust fall quantity. The other plain areas around the central downtown, including the two centers of large dust fall quantity, formed a belt of large dust fall quantity. An obvious belt of small dust fall quantity was formed in the northwestern mountain area. Thus, the spatial distribution of dust fall in Beijing generally shows a structural
Environ Sci Pollut Res
feature of three loops. The difference of dust sources is the primary reason for the spatial variation of dust fall quantity. Dust fall quantity in spring correlates with number of days of dust storm, floating dust, and blowing sand, showing the highest correlation with blowing sand. Dust fall quantity in spring has a good correlation with number of days of moderate and severe atmospheric pollution. Four major sources contribute to dust fall in spring of Beijing. Soil dust produced by farmland soil wind erosion is the leading source. Construction dust is the second contributor, and its percentage content in suburban areas is significantly higher than that in urban area; automobile exhaust dust is the third causing large dust fall in urban area and small ones in the suburban areas. Coal dust is the last source, causing dust fall in suburban areas more than that in urban area. Acknowledgments This work was financially supported by the National Natural Science Foundation of China (Grants No. 41330746 and No. 41101251) and Supported by CERS-China Equipment and Education Resources System (Grant CERS-1-109). The authors greatly appreciate the assistance of Analytical and Testing Center in Beijing Normal University for sample element analyzing, English Editing Elsevier Webshop for language editing, Dr. Ruxing Wang, and Dr. Jifeng Li at Beijing Normal University for help in drawing figures.
References Beijing Municipal Environmental Protection Bureau (2010) Beijing environmental quality bulletin (2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009). 2010-06-07 Available from: http://www. bjepb.gov.cn/bjepb/323474/324034/324735/index.html Chan C-Y, Xu X-D, Li Y-S et al (2005) Characteristics of vertical profiles and sources of PM2.5, PM10 and carbonaceous aerosols in Beijing. Atmos Environ 39:5113–5124 Chen G-T (2001) History of strong dust storms in Beijing and ecological environmental change in nearby regions. J Desert Res 21(4):402– 407 (In Chinese) Chen G-T, He D-L, Song J-X (1989) An approach to the dustfall constituents and their origin. J Desert Res 9(3):25–29 (In Chinese) Chen X-Q, Tan W-K, Liu D-P (2003) Spatial and temporal distribution of bare land in the plain areas of Beijing. Res Soil and Water Cons 10(3):18–25 (In Chinese) China Meteorological Administration (2010) Chinese meteorological data sharing service system. 2010-12-31 Available from: http:// cdc.cma.gov.cn/dataSetDetailed.do Chow J-C, Watson J-G, Ashbaugh L-L (2003) Similarities and differences in PM10 chemical source profiles for geological dust from the San Joaquin Valley, California. Atmos Environ 37(9-10):1317–1340 Chow J-C, Watson J-G, Hampden K (2004) Source profiles for industrial, mobile, and area sources in the big bend regional aerosol visibility and observational study. Chemosphere 54(2):185–208 Dong X-L, Liu D-M, Yuan Y-S (2007) Pollution characteristics and influencing factors of atmospheric particulates in Beijing during the summer of 2005. Chinese J Environ Eng 1(9):100–104 (In Chinese) Fan S-B, Tian G, Li G (2009) Road fugitive dust emission characteristics in Beijing during Olympics game 2008 in Beijing. China Atmos Environ 43:6003–6010 Gao Q-X, Su F-Q, Ren Z-H (2002a) The dust weather of Beijing and its impact. China Environ Sci 22(5):468–471 (In Chinese)
Gao Q-X, Su F-Q, Ren Z-H, et al. (2002) The dust storm of Beijing and its impact on air quality. Report of China scientific association meeting on reducing natural disasters (In Chinese) Guo L-L (2008) Physical and chemical properties and source apportionment of atmospheric dustfall and road dust. PhD Thesis in Beijing Normal University (in Chinese) Guo J-H, Kenneth A-R, Zhuang G-S (2004) A mechanism for the increase of pollution elements in dust storms in Beijing. Atmos Environ 38:855–862 Guo J, Xu Q, Jing W-H (2006) The changing law and trend of dustfall in Beijing during the recent years. Environ Monitor China 22(4):49– 52, In Chinese Han L-H, Zhuang G-S, Cheng S-Y (2007) Characteristics of resuspended road dust and its impact on the atmospheric environment in Beijing. Atmos Environ 41:7485–7499 Hopke P-K, Gladney E-S, Gordon G-E (1976) The use of multivariate analysis to identify sources of selected elements in the Boston urban aerosol. Atmos Environ 10:1015–1025 Li L-J, Gao Q-X (2001) Source analysis of Beijing sand-dust in 2000. Res Environ Sci 14(2):1–3, In Chinese Loska K, Cebula J, Pelczar J (1997) Use of enrichment and contamination factors together with geoaccumulation indexes to evaluate the content of Cd, Cu and Ni in the Rybnik water reservoir in Poland. Water, Air, Soil Pollution 93(4):347–365 Manoli E, Voutsa D, Samara C (2002) Chemical characterization and source identification appointment of fine and coarse air particles in Thessaloniki. Greece Atmos Environ 36:949–961 Reimann C, Caritat P (2000) Intrinsic flaws of element enrichment factors (EFs) in environment algeo chemistry. Environ Sci Technol 34:5084–5091 Song Y, Zhang M, Cai X (2006a) PM10 modeling of Beijing in the winter. Atmos Environ 40:4126–4136 Song Y, Zhang Y, Xie S-D (2006b) Source apportionment of PM2.5 in Beijing by positive matrix factorization. Atmos Environ 40:1526–1537 State Environmental Protection Administration (2000) Background information for revision of law of the People’s Republic of China on the prevention and control of atmospheric pollution (in Chinese). China Environmental Science Press, Beijing State Environmental Protection Administration (2004) Report on the state of the environment in China (in Chinese). Available from: < www. sepa.gov.cn/eic/649368307484327936/20050602/8209.shtml > Sun L-L, Long T, Long Y-F (2008) Source apportionment of atmospheric particulate with an area in Wuhan City by using CMB receptor model and factor analysis. J Saf Env 8(6):94–100, In Chinese Tian S-L, Xia D-S, Yu Y (2011) Magnetic property of dustfall in a Northwest China valley city and its environmental implications. Environ Sci 32:2761–2768 Watson J-G, Chow J-C (2000) Reconciling urban fugitive dust emissions inventory and ambient source contribution estimates: summary of current knowledge and needed.reno: Desert Research Institute of University and Community College System of Nevada, 10-12 Yang D-Z, Yan P, Xu X-D (2002) Aerosol characteristics of Beijing sandstorm. J Appl Meteorol 13:185–194, In Chinese Yatkin S, Bayram A (2008) Determination of major natural and anthropogenic source profiles for particulate matter and trace elements in Izmir, Turkey. Chemosphere 71(4):685–696 Ye D-Z, Chou J-F, Liu J-Y (2000) Causes of sand- stormy weather in northern China and control measures. Acta Geograph Sin 55(5): 513–521, In Chinese Zhang R-J, Wang M-X, Pu Y-F (2000) Analysis on the chemical and physical properties of “2000.4.6” super dust storm in Beijing. Climatic Environ Res 5:259–266, In Chinese Zhao P-S, Feng Y-C, Zhu T (2006) Characterizations of resuspended dust in six cities of North China. Atmos Environ 40:5807–5814 Zhuang G-S, Guo J-H, Yuan H-Y (2001) The compositions, sources, and size distribution of the dust storm from China in spring 2000 and its impact on the global environment. Chinese Sci Bull 46:895–901, In Chinese
RESEARCH ARTICLE
Spatial distribution and source apportionment of atmospheric dust fall at Beijing during spring of 2008–2009 Rende Wang & Xueyong Zou & Hong Cheng & Xiaoxu Wu & Chunlai Zhang & Liqiang Kang
Received: 22 May 2014 / Accepted: 8 September 2014 # Springer-Verlag Berlin Heidelberg 2014
Abstract Beijing is a megacity, where atmospheric dust fall amount is great, and its resultant air pollution is serious. So, analyzing the chemical elements in atmospheric dust fall and revealing its various sources can provide a scientific basis for taking effective measures to improve atmospheric environmental quality. In this paper, we investigated the spatial and temporal distribution of dust fall in Beijing, based on the dust samples collected in the spring of 2008 and 2009 at 18 observation sites laid out in Beijing and then analyzed the sources of atmospheric dust fall based on the test of samples, adopting enrichment factor and factor analysis methods. Our results found that the dust fall quantity in the observation periods was respectively 33.6230 t km−2 and 28.7130 t km−2; the dust fall quantity varied significantly in different months in the spring, but the variation trend was similar at the sites. There were two centers of large quantity in Beijing; one was in the southwest of downtown, and the other was in the northeast of downtown. The spatial distribution of dust fall generally showed a structural feature of three loops; the northwestern mountainous area was a small quantity belt; the plain area around the downtown was a large quantity belt, and the central downtown was a center of small quantity. Soil dust, construction dust, coal dust, and vehicle exhaust were Responsible editor: Constantini Samara R. Wang : X. Zou (*) : H. Cheng : X. Wu : C. Zhang : L. Kang State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Xinjiekouwai Street No.19, Beijing 100875, China e-mail: [email protected] R. Wang Institute of Geographical Sciences, Hebei Academy of Sciences, Shijiazhaung 050021, China X. Wu College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
the four major sources of dust fall in spring of Beijing, respectively, accounting for 38.50, 22.25, 14.06, and 20.82 % of the total dust fall quantity. Keywords Beijing . Atmospheric dust fall . Spatial distribution . Source apportionment
Introduction In the last three decades, with the rapid growth of China’s economy, acceleration of urbanization, and rapid increase of energy consumption and car ownership, urban air pollution is on the rise (State Environmental Protection Administration 2004). In most Chinese cities, atmospheric particulates are the primary pollutant affecting urban air quality (State Environmental Protection Administration 2000). Beijing, as a megacity with the population of over 18 million, is also facing serious atmospheric particulate pollution (Chan et al. 2005). Especially in the spring, not only do motor vehicles, construction sites and roads, catering industry, coal heating and industrial plants discharge large amounts of particulate pollutants, but also strong monsoon brings a lot of dust from inside and outside of Beijing (Zhuang et al. 2001; Dong et al. 2007), so the atmospheric particulates in Beijing have many emission sources, leading to atmospheric particulate pollution and threat to residents’ health (Zhao et al. 2006). Atmospheric dust fall is one of the important indices for urban atmospheric environment monitoring, and it can reflect the seriousness of atmospheric particulate pollution (Guo et al. 2006). Analysis of the physical and chemical characteristics of urban atmospheric dust fall and the sources of particulates have important reference values in control of urban atmospheric particulate pollution (Guo 2008; Tian et al. 2011). Researches on atmospheric dust fall in Beijing were carried out earlier (Chen et al. 1989) and especially the several strong
Environ Sci Pollut Res
dust storms occurring in the spring of 2,000, making the researches increasingly focused on. By analyzing the physical and chemical characteristics of atmospheric dust fall caused by a single dust storm, researchers could discriminate the sources of particulates and their effects on environment (Zhang et al. 2000; Gao et al. 2002a, b; Guo et al. 2004). In recent years, with the rapid increase of car ownership and urban construction expansion, studies on automobile emissions and dust reentrainment on construction sites and roads have attracted more and more attention (Han et al. 2007; Fan et al. 2009). Overall, existing studies are mostly based on the results of a singular sampling site and lack a comprehensive understanding of the dust fall characteristics in the entire region of Beijing, as well as dust source apportionment. In fact, Beijing, a megacity located in northern China, often suffers from the invasion of strong wind, bringing dust and sand in spring, and dust pollution occupies a large proportion of moderate and severe pollution. By source apportionment of atmospheric dust, we not only can learn about the impact of manmade pollution sources on atmospheric environment, but also about the harm to atmospheric environment caused by dust storms, which is a essential supplement to studies on fine particulate matters (PM10 and PM2.5) (Song et al. 2006a; b). Based on the reasons above, we investigated the characteristics and the sources of atmospheric dust fall from March to May in 2008 and 2009.
Methods Collection of dust samples Totally 18 sampling sites were arranged in Beijing (Fig. 1), among which six sampling sites, namely Haidian, Men toug ou, Chao yan g, Tongz hou , Fen gtai, a nd Guanxiangtai, were located in the urban area or suburban plain area; six sampling sites, namely Changping, Shunyi, Huairou, Pinggu, Daxing, and Fangshan, were located in the outer suburban plain area; two sampling sites, namely Yanqing and Miyun, were located in the transition area of outer suburban plain and mountains; and four sampling sites, namely Yanqing Foyeding, Huairou Tanghekou, Miyun Shangdianzi, and Zhaitang, were located in the outer suburban mountains area. Sampling devices were installed in standard meteorological observation stations affiliated with The Beijing Meteorological Bureau; the ground of the observation fields was artificial grass and not shielded by surrounding buildings and trees, and the surrounding environment of the sampling sites was same. Each sampling site was installed with two sets of dust collecting devices with the distance of 2 m. The dust collecting device was mainly composed of dust collecting glass cylinder and steel bracket. The glass cylinder was
60 cm in height and 30 cm in diameter and fixed on a bracket 0.9 m above the ground, and the glass cylinder port was 1.5 m above the ground, equivalent to the height of mouth and nose of ordinary people (Fig. 2). The sampling time was from March to May in 2008 and 2009. The sampling frequency of the two sets of devices at each sampling site was different. One set collected samples at 17:00 every 10 days and the other collected samples, at 17:00 at the end of every month. In this paper, we analyzed the dust collected monthly in the spring of 2008 and 2009. No material was added into glass cylinders, and we rinsed the inner wall of the cylinder with distilled water when sampling, poured the turbid liquid into a clean wild-mouth bottle, and repeated several times, until the inner wall and bottom of the cylinder were rinsed clean. After sampling, we covered the bottle with a cap, filled in the label, and placed it in a dry and cool place for later handling. Sample handling and testing We poured the turbid liquid of the collected dust sample into a beaker, placed it in an oven, and dried it constant at 60 °C; we used a brush to clean out the dust sample in the beaker, placed it into a plastic sample bag that was weighed and labelled, weighed it with a 1/1,000 electronic balance again, and calculated the net weight of each sample collected. We used an ULTIMA inductively coupled plasma spectrometer (ICP-MS) produced by French JY Company to analyze the contents of 17 elements, namely Al, As, Ba, Ca, Co, Cr, Cu, Fe, Mg, Mn, Ni, P, Pb, Ti, V, Zn, and S, in the dust samples, with the analytical precision of 0.01 μg g−1. The test was made in the Analysis and Testing Center in Beijing Normal University. Figure 3 shows the experiment procedure in detail. We used the same method to measure the contents of the elements in the blank sample and obtained the true contents of the elements in the sample by the measured contents of the elements minus the contents in the blank sample. Dust source apportionment In this study, enrichment factor method and factor analysis method were adopted to analyze the sources of dust particulates. Enrichment factor method Enrichment factor method is to compare the contents of elements in dust particulates and known particulates, analyze the degree of enrichment of elements in particulates, and determine whether particulates are from known substances; it is a qualitative method in source apportionment (Reimann and Caritat 2000). This method is generally combined with quantitative analytical methods to make mutual authentication. The
Environ Sci Pollut Res
Fig. 1 Distribution of dust fall sampling sites
formula is: ðCi=C R dustfall Ef ¼ 0. Ci background 0
ð1Þ
CR
Where Ci and CR are contents of element i and R in dust fall; C′i and C′R are contents of element i and R in soil (Table 1). R is a reference element, and in this paper, Al was selected as the reference element. When Ef≤1, it is considered that an element is from the natural source, for the reference element Ef=1; when 110, it is considered that an element is from the artificial source (Loska et al. 1997).
Factor analysis method Factor analysis method can not only qualitatively identify the sources of atmospheric particulates, but also quantitatively calculate the contribution of each source to the total particulate pollutants, and it is an analysis method commonly used in dust fall source apportionment (Sun et al. 2008). Principle of factor analysis method is to attribute some variables or samples with complex relationships to several comprehensive factors, on the basis of the recognition that certain correlation exists between the variables related with pollution sources and in the condition of no loss of main information (Hopke et al. 1976), and it can be expressed as the following formula: X ji ¼ a j1 F 1i þ a j2 F 2i þ ⋅⋅⋅ þ ajp F pi þ d j U ji
Fig. 2 Dust fall samplers (marked in ovals)
ð2Þ
Where Xji is a linear combination of factor Fji (applicable to all the variables) and unique factor Uji (applicable to each variable), aji is a factor load coefficient to each variable, and dj is a standard regression coefficient to unique variable j. The main purpose of factor analysis is to obtain factor load coefficient aji of common factor. The value of factor load coefficient reflects the degree of correlation between factor and variable. This method is to make calculations with the actually measured contents of elements in dust fall particulates and make analysis by combining the specific situation in
Environ Sci Pollut Res
Step 1: Adding acid Place 0.1g dried dust sample into a digestion tank. Add 5.0ml HNO3. Add 2.0ml HCl and 1.0ml HF.
Step 2: Digestion Digestion at 150 ć for 6 hours.
Step 3: Evaporation Open the lid. Place the sample solution in a ventilated hood. Dry to one drop.
Step 4: Constant volume Add 1.0 ml HClO3. Transfer the solution into a test tube.
Step 5: Dilution Dissolve to the volume of 100ml.
Step 6: Test Directly use the HR-ICP-MS method to measure the contents of the elements.
constant
Fig. 3 The procedure of analyzing the contents of elements using inductively coupled plasma spectrometer (ICP-MS)
Beijing, to obtain the main sources of dust fall substances and their contribution rates.
In 2008, the dust fall quantity in March, April, and May was respectively 6.99, 10.03, and 16.61 t km−2, accounting for respectively 21.79, 29.83, and 49.38 % of the total dust fall quantity in the spring, and the dust fall quantity was largest in May and smallest in March. Among the 18 sampling sites, 17 sites had the same feature of the monthly variation, and only at Haidian site was the dust fall quantity in March larger than that in April. In 2009, the dust fall quantity in March, April, and May was respectively 6.59, 12.73, and 9.38 t km−2, accounting for respectively 22.96, 44.35, and 32.69 % of the total dust fall quantity in the spring, and the dust fall quantity was largest in April and smallest in March. Among the 18 sampling sites, 14 sites had the same feature of the monthly variation; only at Foyeding and Shangdianzi sites in the northern mountain area
Results Features of dust fall Dust fall quantity In 2008, the atmospheric dust fall quantity in the spring of Beijing was 21.74–48.43 tons per square kilometers (t km−2), averagely 33.63 t km−2. In 2009, it was 13.98–39.81 t km−2, averagely 28.71 t km−2 (Fig. 4). Table 1 Average content of elements in topsoil around Beijing city Elements
Al
As
Ba
Ca
Cd
Co
Cr
Cu
Fe
Average content (μg g−1) Standard deviations Elements Average content (μg g−1) Standard deviations
36,733.93 5,286.54 Mg 7,333.67 642.55
19.55 4.25 Mn 741.44 25.36
1,223.22 95.43 Ni 49.43 1.99
1,4076.17 496.81 P 695.65 31.53
1.04 0.19 Pb 39.68 4.32
44.11 3.86 Ti 3951.33 221.67
152.69 3.94 V 127.01 17.43
32.56 1.93 Zn 100.52 34.70
2,5427.65 882.88 S 239.70 21.14
The average of 40 topsoil samples in Beijing
Environ Sci Pollut Res
quantity around the central downtown. The central downtown was the center of small dust fall quantity. The dust fall quantity in the northwestern mountain area was smaller, forming an obvious belt of small dust fall quantity around the northwest of the central downtown. Overall, the spatial distribution of dust fall in Beijing generally showed a structural feature of three loops; the northwestern mountainous area was a small quantity belt, forming the outer loop; Fengtai, Mentougou, Changping, Shunyi, Tongzhou, Daxing, and Fangshan, located in the plain area around the downtown, which was a large quantity belt, forming the middle loop; the inner loop covered most part of the central downtown, which was the center of small quantity (Fig. 5). Relationship between dust fall and dust storm The statistical results showed that the dust fall quantity was significantly larger in years with relatively large number of dust weather days in the spring of 2000–2009 (Fig. 6, Table 2). Dust fall quantity in spring had certain correlation with interannual variations of number of floating dust days and blowing sand-dust days. This indicated that dust weathers, especially blowing sand-dust, have important influence on spring dust fall quantity in Beijing. Atmospheric dust fall and pollution Fig. 4 Spring dust fall amount at different sampling sites in 2008 (a) and 2009 (b)
was the dust fall quantity in March larger than that in May, and at Tongzhou and Miyun sites, the dust fall quantity was largest in May and smallest in March. Spatial distribution of dust fall The spatial distribution of dust fall quantity was quite different. In the spring of 2008, the dust fall quantity was largest in Fengtai (48.43 t km−2) and smallest in Miyun Shangdianzi (21.74 t km−2). In the spring of 2009, the dust fall quantity was largest in Tongzhou (39.81 t km−2) and smallest in Yanqing Foyeding (13.98 t km−2). There were two centers of large dust fall quantity in Beijing (Fig. 5). One was in the southwest of the city, centered by Fengtai, including parts of Fengtai District, Mentougou District, Fangshan District, and Shijingshan District; the other was in the northeast of the city, centered by Shunyi, including parts of Shunyi District, Miyun District, Huairou District, and Tongzhou District. In addition to the two areas with large dust fall quantity, Changping, Daxing, and several other plain areas also had relatively large dust fall quantity and connected with the above-mentioned two areas, forming a belt of large dust fall
The statistical result showed that there was good correlation between dust fall quantity and number of days of moderate and severe atmospheric pollution in the spring of 2000–2009 (Fig. 7), and the indicator of dust fall quantity could generally reflect the atmospheric pollution in spring of Beijing. Further analysis also showed that atmospheric pollution in spring of Beijing was mainly caused by blown sand and dust (Table 2); the number of days of dust pollution accounted for 42.9– 100 % of the number of days of moderate to severe pollution in the spring of 2000–2009, and the correlation coefficient reached 0.814. Dust fall source apportionment Enrichment of elements in dust fall With the contents of elements in topsoil in Beijing as the background values (Table 1) and Al as the reference element, the analysis on the degree of enrichment of various elements in dust by enrichment factor method showed that the elements with the enrichment factor 10 included only S (Fig. 8). The elements with the enrichment factor close to 1 in atmospheric
Environ Sci Pollut Res
Fig. 5 Spatial distribution of spring dust fall amount in 2008 (a) and 2009 (b)
particulates mainly include soil wind erosion products, and if enrichment factor >10, then the element is enriched, mainly from various pollution elements caused by human activities. For elements with the enrichment factor in 1–10, manmade pollution also takes a certain proportion (Manoli et al. 2002). Accordingly, it is considered that Al, Ba, Co, Cr, Fe, Mn, Ni, Ti, and V are not enriched and mainly from the soil in Beijing or in its adjacent regions; S is significantly enriched in atmospheric dust fall due to human activities and mainly manmade pollution sources; As, Ca, Cu, Mg, P, Pb, and Zn are partly from the soil, but human activities have significant effects on enrichment of these elements. Fig. 6 Correlation of spring dust fall and dust days
Dust fall source apportionment Analysis on correlations among 17 elements in dust showed that Al, Ba, Fe, Ti, and V were significantly correlated, with the correlation coefficient above 0.8 and the enrichment factor ≤1, and mainly from soil dust (Chow et al. 2003); As and S were typical identification elements in coal dust; the correlation coefficient was the highest (0.68), and their enrichment factors were significantly greater than 1, mainly from coal combustion discharge (Yatkin et al. 2008); Cu, Zn, and Cr had good correlations; the correlation coefficient was above 0.65, and the enrichment factors of these elements were in 1–10,
Environ Sci Pollut Res Table 2 Dust days, severe pollution days, and spring dust fall amount from 2000 to 2009 Year
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
Dust fall amount in suburban area (t km−2) Blowing sand-dust daysc Floating dust daysc Moderate and severe pollution days (days)d Dust pollution daysd
71.1a 14 8 13 11
66.6 a 11 13 15 12
66.3 a 21 8 11 10
39.9 a 1 0 2 1
43.8 b 6 1 7 3
38.4 b 7 4 8 4
60.3 b 15 9 14 9
42.6 b 4 5 2 2
35.4 9 6 7 6
32.3 3 2 1 1
a
From Guo et al. (2006)
b
From Guo (2008)
c
From China Meteorological Administration (2010)
d
From Beijing Municipal Environmental Protection Bureau (2010)
indicating that they were affected by manmade sources (Table 3). Cu, Zn, and Cr were mainly from combustion, waste incineration, and metal smelting, so they could be regarded as the identification elements of incineration and smelting dust (Watson and Chow 2000); Ca and Mg had relatively high correlation coefficients, and their enrichment factors were significantly greater than 1, among which Ca was mainly from emissions from construction processes and was the main identification element of construction cement dust, and Mg was a common element in soil dust and construction dust (Chow et al. 2004); Pb and Mn had a relatively high correlation coefficient, reaching 0.98, among which Pb was mainly from automobile exhaust and the identification element of automobile exhaust dust (Ho et al. 2003), and these two elements were certainly correlated with Al, Fe, V, and other soil identification elements, indicating that these two elements were partly from soil dust. The other three elements, Co, P, and Ni, had certain correlations with other elements, but the correlation coefficients were not high, indicating that the sources were relatively complex, among which Co might be Fig. 7 Correlation of spring dust fall and pollution days
from soil dust and fuel, P might be from coal dust and metallurgical dust, and Ni might be from soil dust and coal dust (Watson and Chow 2000). Accordingly, eight elements, Al, Ti, Ca, Cu, Pb, Mg, Fe, and As, selected from the measured 17 elements, were regarded as the identification elements of various sources. The identification elements of various emission sources were respectively Al, Ti, and Fe for soil dust; As for coal dust; Ca and Mg for construction cement dust; Pb for automobile exhaust dust; and Cu for incineration and smelting dust. Factor analysis function in Statistical Product and Service Solutions (SPSS 11.5) was used to make source apportionment of dust collected respectively in urban and suburban areas. For areas with clean atmosphere, initial load factor matrix is generally selected; for areas with polluted atmosphere, rotated load matrix should be selected (Song et al. 2006b). Atmospheric pollution was relatively serious in spring of Beijing, so the initial factor load matrix should be made using Varimax rotation in order to obtain the rotated factor matrix. Then the rotated factor matrix was made
Environ Sci Pollut Res
Fig. 8 Enriching factor of element in spring dust fall in March (a), April (b), and May (c) of 2008 and in March (d), April (e), and May (f) of 2009
regularization reduction to obtain the ultimate factor load matrix of dust in each month, and by analysis and interpretation, the main sources of dust and their contribution rates were determined. The final results showed that soil dust, construction dust, coal dust, and automobile exhaust were four major sources of dust in spring of Beijing, accumulatively accounting for more than 90 % of the total dust sources (Table 4). Among which, soil dust from farmland by wind erosion was
the leading source of dust fall, accounting for 26.88–50.23 % of the dust fall quantity in each month and was the primary source in most months. Construction dust occupied a certain proportion in each month and was even the primary source in some months. Automobile exhaust dust occupied a relatively large proportion in urban area and was even the primary source in some months; it occupied a relatively small proportion in suburban areas and was even not a main component of
Environ Sci Pollut Res Table 3 Correlation matrix of different elements
Al As Ba Co Cr Cu Fe Mg Mn Ni P Pb Ti V Zn Ca S
Al
As
Ba
Co
Cr
Cu
Fe
Mg
Mn
Ni
P
1.00 −0.51 0.81 0.61 0.29 0.41 0.99 0.17 0.58 0.55 −0.52 0.69 0.86 0.98 0.31 −0.46 −0.51
1.00 −0.02 −0.56 0.38 0.14 −0.57 −0.82 −0.48 0.29 0.38 −0.50 −0.51 −0.38 0.09 −0.45 0.68
1.00 0.55 0.47 0.55 0.78 −0.19 0.19 0.84 −0.35 0.28 0.70 0.85 0.27 −0.80 −0.25
1.00 0.02 0.58 0.57 0.27 0.17 0.08 0.09 0.17 0.49 0.53 0.19 0.00 −0.06
1.00 0.67 0.25 −0.35 −0.29 0.62 0.10 −0.12 0.46 0.45 0.88 −0.72 0.05
1.00 0.30 −0.45 0.00 0.28 0.50 0.05 0.29 0.47 0.77 −0.38 0.45
1.00 0.27 0.56 0.55 −0.62 0.68 0.90 0.97 0.25 −0.44 −0.62
1.00 −0.02 −0.22 −0.48 0.04 0.44 0.08 −0.22 0.70
1.00 −0.10 −0.32 0.98 0.20 0.49 −0.08 0.14
1.00 −0.51 0.04 0.63 0.66 0.24 −0.98
1.00 −0.42 −0.62 −0.51 0.31 0.35
−0.74
−0.18
−0.38
0.53
dust fall in some months, which was related with more vehicles in urban area and less vehicles in suburban areas. In most months, the content of coal dust in suburban areas was higher than that in urban areas, which was related with more industrial enterprises and residential heating using a lot of coal in suburban areas. Dust fall in most months, especially in urban areas, did not contain dust produced by waste incineration and metal smelting, which benefited from elimination of a large number of polluting enterprises, coal dust, and vehicle exhaust.
Pb
Ti
V
Zn
Ca
1.00 0.38 0.63 0.06 0.01
1.00 0.89 0.41 −0.51
1.00 0.42 −0.59
1.00 −0.35
1.00
−0.31
−0.73
−0.49
0.16
0.20
S
1.00
Discussions Dust fall quantity in the spring of 2008 was significantly larger than that in 2009, about 1.1 times of that in 2009, which might be related with more days of dust storm in the spring of 2008 than in 2009. According to the meteorological data (Table 2), totally 15 times of dust storm occurred in Beijing in the spring of 2008 and only five times in 2009, and dust storm brought a large quantity of particulates. The results of dust source apportionment also showed that the content of soil dust in the
Table 4 Contribution to spring dust fall from main sources in 2008 and 2009 Time (year, month)
2008, 03 2008, 04 2008, 05
Region
Soil dust
Construction dust
Coal dust
Vehicle exhaust
Incineration and smelting dust
Total
Urban Suburban Urban Suburban Urban Suburban
40.24 32.93 50.23 50.21 43.53 35.45 42.10
27.74 36.86 13.41 14.68 13.38 18.12 20.70
13.40 15.97 16.29 22.88 13.48 8.54 15.09
14.63 13.53 18.80 12.23 29.09 21.78 18.34
– – – – – 16.11 2.69
96.01 99.29 98.73 100.00 99.48 100.00 98.92
Urban Suburban Urban Suburban Urban Suburban
34.09 47.65 33.48 34.25 33.06 26.88 34.90
24.07 25.41 28.76 29.13 15.80 19.60 23.80
16.63 14.08 – 13.35 – 34.12 13.03
23.50 12.65 22.68 16.48 46.69 17.78 23.30
– – 14.24 – – – 2.37
98.29 99.79 99.16 93.21 95.55 98.38 97.40
Average 2009, 03 2009, 04 2009, 05 Average
Contribution ratio (%)
Environ Sci Pollut Res
spring of 2008 was significantly higher than that in 2009 (Table 4), indicating that dust storm frequency and intensity are important factors affecting atmospheric dust fall quantity in spring of Beijing. The dust fall quantity was quite different at each observation site in different months, but the trend of inter-monthly variation of dust fall quantity in spring is almost similar. In 2008, among the 18 observation sites, 17 sites showed the largest dust fall quantity in May, followed by April, and smallest in March; in 2009, among the 18 sites, 14 sites showed the largest dust fall quantity in April, followed by May, and smallest in March, indicating that dust fall intensity in various areas in Beijing was affected by common factors. Coal dust, automobile exhaust dust, and construction dust were local dust sources, had relatively small range of influence, and would not extensively affect the dust fall quantity in Beijing, so the frequencies of strong winds and dust storms in different months might be the main cause affecting the intermonthly variation of dust fall quantity in spring. The different trend of variation of dust fall quantity at few sites might be affected by local dust sources or caused by human factors. The dust fall quantity is always relatively large in the southwest and northeast of Beijing, and they are the centers of large dust fall quantity, which might be related with nearsurface atmospheric circulation and the coupling effects of underlying surface. The analysis on near-surface airflow field shows that northwest wind is prevalent from March to May every year in Beijing, and the wind enters the southeast plain area after crossing the low ridges in Badaling and Qingshuiding and jointly affected by wind field divergence and mountain obstruction, forms a closed circulation respectively in the northeast and the southwest, with the middle air passage as the boundary. The northeast circulation is centered by Shunyi, covering the mountain front areas in Shunyi, Pinggu, Huairou, Miyun, and several other districts. The southwest circulation is centered by Fengtai, covering the mountain front areas in Fengtai, Fangshan, Shijingshan, Mentougou, and several other districts (Zhao et al. 2006). In the circulations, air activity is weak and easy to form downdraft, which is conducive to settling of particulates. In addition, Fengtai and Mentougou are centralized industrial regions in Beijing, and large quantity of particulate pollutants emitted from industrial production is bound to increase dust fall. The northeast is distributed with large areas of farmland, and soil wind erosion provides a large amount of material bases for dust fall. Small dust fall quantity in the northwestern mountainous area is due to large vegetation coverage, limited surface dust quantity, and long distance to urban area; it is less affected by manmade pollution sources, and dust fall is mainly from the longdistance transportation by upwind from outside of Beijing (Zhuang et al. 2001). The dust fall quantity in the urban areas is relatively small (Fig. 5), which might be related with hard ground and lack of soil dust sources in the urban areas.
In the four major sources of dust fall, soil dust takes the largest share. According to different sources, soil dust can be divided into outside soil dust and inside soil dust. Outside soil dust is carried by wind from outside of Beijing, and its affecting range is very big, but regional difference is small. Inside soil dust is mainly from bare farmland around Beijing (Chen et al. 2003), and its main affecting range is mainly in the surrounding area of farmland. Currently, there is still some controversy on the issue of contribution of inside and outside dust sources to the dust fall in Beijing (Li and Gao 2001; Gao et al. 2002a, b). Existing study results show that floating dust and dust storm particulates are mainly from outside, and blown dust particulates are mainly from inside sources (Ye et al. 2000; Yang et al. 2002). Among the days of dust weather in Beijing in recently 50 years, floating dust and dust storm account for respectively 20 and 9 %, and the remaining 71 % is blowing sand (Chen 2001). It can be seen that the local soil dust in Beijing is also an important source of atmospheric dust particulates. For reducing atmospheric particulate pollutants, in addition to continuing to strengthen the comprehensive control of the ecological environment of outside dust sources, we must also do well in control of local dust sources in Beijing. Construction dust is the second largest source of dust fall in Beijing, and it is mainly produced in illegal discharges during construction. In recent years, most construction projects in Beijing are in the suburbs, and the percentage content of construction dust in suburban areas is significantly higher than that in the central downtown. Automobile exhaust dust occupies a relatively large proportion of dust fall in urban area and a relatively small proportion in the suburban areas, which is directly related with higher density of vehicles in the urban areas and lower density in suburban areas. In most months, the content of coal dust in suburban areas is higher than that in urban areas, which is related with more industrial enterprises and larger coal consumption for residential heating in suburban areas.
Conclusions The dust fall quantity in Beijing in the spring of 2008 was significantly larger than that in 2009, due to more days of dust storm in the spring of 2008 than in 2009. The dust fall quantity varied in different months in spring, but its variation trend is similar, because the dust fall intensity in various regions of Beijing is affected by wide-range wind fields. The central downtown is the center of small dust fall quantity. The other plain areas around the central downtown, including the two centers of large dust fall quantity, formed a belt of large dust fall quantity. An obvious belt of small dust fall quantity was formed in the northwestern mountain area. Thus, the spatial distribution of dust fall in Beijing generally shows a structural
Environ Sci Pollut Res
feature of three loops. The difference of dust sources is the primary reason for the spatial variation of dust fall quantity. Dust fall quantity in spring correlates with number of days of dust storm, floating dust, and blowing sand, showing the highest correlation with blowing sand. Dust fall quantity in spring has a good correlation with number of days of moderate and severe atmospheric pollution. Four major sources contribute to dust fall in spring of Beijing. Soil dust produced by farmland soil wind erosion is the leading source. Construction dust is the second contributor, and its percentage content in suburban areas is significantly higher than that in urban area; automobile exhaust dust is the third causing large dust fall in urban area and small ones in the suburban areas. Coal dust is the last source, causing dust fall in suburban areas more than that in urban area. Acknowledgments This work was financially supported by the National Natural Science Foundation of China (Grants No. 41330746 and No. 41101251) and Supported by CERS-China Equipment and Education Resources System (Grant CERS-1-109). The authors greatly appreciate the assistance of Analytical and Testing Center in Beijing Normal University for sample element analyzing, English Editing Elsevier Webshop for language editing, Dr. Ruxing Wang, and Dr. Jifeng Li at Beijing Normal University for help in drawing figures.
References Beijing Municipal Environmental Protection Bureau (2010) Beijing environmental quality bulletin (2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009). 2010-06-07 Available from: http://www. bjepb.gov.cn/bjepb/323474/324034/324735/index.html Chan C-Y, Xu X-D, Li Y-S et al (2005) Characteristics of vertical profiles and sources of PM2.5, PM10 and carbonaceous aerosols in Beijing. Atmos Environ 39:5113–5124 Chen G-T (2001) History of strong dust storms in Beijing and ecological environmental change in nearby regions. J Desert Res 21(4):402– 407 (In Chinese) Chen G-T, He D-L, Song J-X (1989) An approach to the dustfall constituents and their origin. J Desert Res 9(3):25–29 (In Chinese) Chen X-Q, Tan W-K, Liu D-P (2003) Spatial and temporal distribution of bare land in the plain areas of Beijing. Res Soil and Water Cons 10(3):18–25 (In Chinese) China Meteorological Administration (2010) Chinese meteorological data sharing service system. 2010-12-31 Available from: http:// cdc.cma.gov.cn/dataSetDetailed.do Chow J-C, Watson J-G, Ashbaugh L-L (2003) Similarities and differences in PM10 chemical source profiles for geological dust from the San Joaquin Valley, California. Atmos Environ 37(9-10):1317–1340 Chow J-C, Watson J-G, Hampden K (2004) Source profiles for industrial, mobile, and area sources in the big bend regional aerosol visibility and observational study. Chemosphere 54(2):185–208 Dong X-L, Liu D-M, Yuan Y-S (2007) Pollution characteristics and influencing factors of atmospheric particulates in Beijing during the summer of 2005. Chinese J Environ Eng 1(9):100–104 (In Chinese) Fan S-B, Tian G, Li G (2009) Road fugitive dust emission characteristics in Beijing during Olympics game 2008 in Beijing. China Atmos Environ 43:6003–6010 Gao Q-X, Su F-Q, Ren Z-H (2002a) The dust weather of Beijing and its impact. China Environ Sci 22(5):468–471 (In Chinese)
Gao Q-X, Su F-Q, Ren Z-H, et al. (2002) The dust storm of Beijing and its impact on air quality. Report of China scientific association meeting on reducing natural disasters (In Chinese) Guo L-L (2008) Physical and chemical properties and source apportionment of atmospheric dustfall and road dust. PhD Thesis in Beijing Normal University (in Chinese) Guo J-H, Kenneth A-R, Zhuang G-S (2004) A mechanism for the increase of pollution elements in dust storms in Beijing. Atmos Environ 38:855–862 Guo J, Xu Q, Jing W-H (2006) The changing law and trend of dustfall in Beijing during the recent years. Environ Monitor China 22(4):49– 52, In Chinese Han L-H, Zhuang G-S, Cheng S-Y (2007) Characteristics of resuspended road dust and its impact on the atmospheric environment in Beijing. Atmos Environ 41:7485–7499 Hopke P-K, Gladney E-S, Gordon G-E (1976) The use of multivariate analysis to identify sources of selected elements in the Boston urban aerosol. Atmos Environ 10:1015–1025 Li L-J, Gao Q-X (2001) Source analysis of Beijing sand-dust in 2000. Res Environ Sci 14(2):1–3, In Chinese Loska K, Cebula J, Pelczar J (1997) Use of enrichment and contamination factors together with geoaccumulation indexes to evaluate the content of Cd, Cu and Ni in the Rybnik water reservoir in Poland. Water, Air, Soil Pollution 93(4):347–365 Manoli E, Voutsa D, Samara C (2002) Chemical characterization and source identification appointment of fine and coarse air particles in Thessaloniki. Greece Atmos Environ 36:949–961 Reimann C, Caritat P (2000) Intrinsic flaws of element enrichment factors (EFs) in environment algeo chemistry. Environ Sci Technol 34:5084–5091 Song Y, Zhang M, Cai X (2006a) PM10 modeling of Beijing in the winter. Atmos Environ 40:4126–4136 Song Y, Zhang Y, Xie S-D (2006b) Source apportionment of PM2.5 in Beijing by positive matrix factorization. Atmos Environ 40:1526–1537 State Environmental Protection Administration (2000) Background information for revision of law of the People’s Republic of China on the prevention and control of atmospheric pollution (in Chinese). China Environmental Science Press, Beijing State Environmental Protection Administration (2004) Report on the state of the environment in China (in Chinese). Available from: < www. sepa.gov.cn/eic/649368307484327936/20050602/8209.shtml > Sun L-L, Long T, Long Y-F (2008) Source apportionment of atmospheric particulate with an area in Wuhan City by using CMB receptor model and factor analysis. J Saf Env 8(6):94–100, In Chinese Tian S-L, Xia D-S, Yu Y (2011) Magnetic property of dustfall in a Northwest China valley city and its environmental implications. Environ Sci 32:2761–2768 Watson J-G, Chow J-C (2000) Reconciling urban fugitive dust emissions inventory and ambient source contribution estimates: summary of current knowledge and needed.reno: Desert Research Institute of University and Community College System of Nevada, 10-12 Yang D-Z, Yan P, Xu X-D (2002) Aerosol characteristics of Beijing sandstorm. J Appl Meteorol 13:185–194, In Chinese Yatkin S, Bayram A (2008) Determination of major natural and anthropogenic source profiles for particulate matter and trace elements in Izmir, Turkey. Chemosphere 71(4):685–696 Ye D-Z, Chou J-F, Liu J-Y (2000) Causes of sand- stormy weather in northern China and control measures. Acta Geograph Sin 55(5): 513–521, In Chinese Zhang R-J, Wang M-X, Pu Y-F (2000) Analysis on the chemical and physical properties of “2000.4.6” super dust storm in Beijing. Climatic Environ Res 5:259–266, In Chinese Zhao P-S, Feng Y-C, Zhu T (2006) Characterizations of resuspended dust in six cities of North China. Atmos Environ 40:5807–5814 Zhuang G-S, Guo J-H, Yuan H-Y (2001) The compositions, sources, and size distribution of the dust storm from China in spring 2000 and its impact on the global environment. Chinese Sci Bull 46:895–901, In Chinese
