JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 106, NO. D13, PAGES 14,501-14,513, JULY 16, 2001

Characteristics of the spatial distribution and yearly variation of aerosol optical depth over China in last 30 years

Luo Yunfeng • and Lu Daren Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China

Zhou Xiuji and Li Weiliang Chinese Academy of Meteorological Sciences, Beijing, China

He Qing Agrometeorology Institute, Chinese Academy of Agricultural Sciences, Beijing, China

Abstract. The yearly and monthly mean aerosol optical depth (AOD) at 0.75 pm were retrieved using a new method improved from Qiu's algorithm from the data of daily direct solar radiation, sunshine duration, surface pressure, and vapor pressure at 46 A class solar radiation stations over China from 1961 to 1990, as well as the Total Ozone Mapping Spectrometer (TOMS) derived ozone data from 1979 to 1990. Then the analysis on the distribution of yearly mean AOD and its variation over China in the last 30 years were made from the derived AOD data. It was found that the yearly mean AOD has pattern related to the geographical features with the maximums over basins. One of the maximum centers at Sichuan Basin, southwest of China, and the other is in the south Xinjiang Basin, northwest of China. In most areas of China the maximum of AOD occurs in spring, but the season of reaching the minimum varies with regions. The monthly mean AOD distributions are similar to the annual mean pattern, having strong "basin" effect, but the month-to-month differences are still obvious. In addition, AOD increased dramatically over China mainland from 1961 to 1990, particularly in the middle and lower reaches area of the Yangzi River and the east part of southwest China. In north China, Shandong peninsula, the east part of Qinghai Province, and coastal areas of Guangdong Province, a significant increasing trend of AOD is shown, while in most parts of northwest China and northeast China, the increase trend is less significant. However, in the western part of Xinjiang autonomous region and part of Yunnan Province, only a decreasing tendency is shown. Of the total 46 stations, the yearly averaged AOD variation curve can be briefly divided into two periods. One period is from 1961 to 1975, when AOD is smaller than the 30 year mean value; the other period is from 1976 to 1990, when AOD is higher than the mean value. Except for the peak in 1982 and 1983, which may be attributed to the eruptions of EI Chichon, the curve shows a significant increasing trend from 1961 to 1990. The monthly averaged AODs of the total 46 stations also obviously increased.

1. Introduction

Global warming has been a hot topic that attracts the attention not only of the scientists but also of the governments and the public. However, in recent years, the analysis of the observational data shows that the patterns of surface temperature change have different characteristics for different regions in the world and in some areas near the highly industrialized regions the surface temperature proved to be decreasing [Intergovernmental Panel on Climate Change (IPCC), 1995; Chen et al., 1991]. Some scientists attribute the differences of surface temperature change for regions to the

•Now at Department of Earth Science, National Natural Science Foundation of China, Beijing, China.

Copyright 2001 by the American Geophysical Union.

Paper number 2001JD900030. 0148-0227/01/2001JD900030509.00

effects of atmospheric aerosols [Liet al., 1995; Engardt and Rodhe, 1993].

Atmospheric aerosol refers to the particles suspended in the atmosphere with diameters <10 !am. Since preindustrial times, human activities have emitted a large amount of polluted aerosol particles into atmosphere, and this emission has been enhanced rapidly since 1950s. The increase of aerosol concentrations affects not only the Earth's environment but also the earth-atmosphere system's energy budget by directly absorbing and backscattering the incoming solar radiation and indirectly modifying the optical properties and lifetimes of clouds, resulting in global and regional climate change [Charlson et al., 1991; Penner et al., 1994; Taylor and Penner, 1994; Chuang et al., 1997]. In recent years, radiative forcing of aerosols has been simulated by many scientists, and its environmental and climate effects have become an important scientific issue [Boucher and Anderson, 1995; Mitchell et al., 1995; Pan et al., 1997; Nemesure et al., 1995; Pilinis et al., 1995; Luo et al., 1999).

14,501

14,502 LUO ET AL.' AEROSOL DISTRIBUTION AND VARIATION IN CHINA

5ON'

40N

'30N'

2ON'

ß :

80E 90E 100E 110E 120E 130E 140E

Longitude

Figure 1. Locations of 46 solar radiation stations in China.

Taylor and Penner' s [ 1994] and Kiehl and Briegleb' s [ 1993 ] simulations showed that in some industry regions in the Northern Hemisphere, such as North America, middle Europe, and East Asia, aerosol's "umbrella effect" may exceed the greenhouse warming effect due to the emission of human activities and lead to the cooling in these areas. Presently, most scientists [Charlson et al., 1992; Kaufman and Chou, 1993] consider that in order to accurately simulate the global or regional climate change, the radiative forcing of atmospheric aerosols should be reasonably included in the global circulation models.

As well known, accurate study of the environment and climate effects due to aerosols depends essentially on the knowledge of its spatiotemporal distribution and the precise estimate of its optical characteristics. However, it is not feasible to achieve the detailed spatial and temporal distribution of aerosols because of the scarcity of the direct observational data of aerosols. Hence, in addition to enhancement of field observation campaign, many scientists have made great effort to derive aerosol information from long history of other recorded meteorological data, such as solar radiation [King et al., 1978; Vasilyev et al., 1995; dacovides et al., 1996; Qiu, 1997; Marenco et al., 1997; Qiu, 1998; Gueyrnard, 1998]. Considering that large-scale direct aerosol observation is infeasible at present and even in the near future, indirectly retrieving aerosol information from other data is quite practicable.

China, the largest developing country in the world, has been using coal as the major energy supply for many years. This makes China one of the areas polluted heavily by sulfate aerosols. After analyzing the direct solar radiation, visibility, and aerosol optical depth of four big cities in the south China coastal area, Luo [2000a] pointed out that compared to the 1980s to 1960s, the total daily direct solar radiation decreased by >20% for all the cities, with the maximum decrease present in Guangzhou (29.2%). The surface visibility decreased >31.6% in Fuzhou, 55.1% in Guangzhou, 27.2% in Haikou, and 29.9% in Nanning. It was observed that the areas of acid rain, which were located discretely in south part of the Yangzi River in the 1960s, have extended to the north of the Yangzi River in the 1990s and covered nearly 40% of China. The economic loss caused by acid sedimentation on agriculture, forestry, and material destruction was estimated over $ 2.5 billion U.S. per year [Wang, 1997]. In addition, the mineral aerosol, which was derived from northwest China, especially in spring, can transfer along with the upper wind to far away

downstream and impact the environment and climate of east China and adjacent areas [Luo et al., 1998]. In fact, direct observation of aerosol in China is very scarce except for a few individual experimental observations. So far, we still lack a quantitative and comprehensive understanding about the geographical distribution and temporal variation of aerosols over China. Therefore the objective of this study is to retrieve the aerosol optical depth (AOD) and then to analyze the characteristics of its mean distribution and yearly variation.

2. Methodology

Aerosol optical depth (AOD) is the most important physical parameter for characterizing aerosols and also one of the key factors for evaluating atmospheric pollution and climate effect due to aerosols. So the precise estimate of AOD is of great importance. In this paper, we employ the daily direct solar radiation and other auxiliary meteorological data to retrieve the yearly and monthly mean AOD.

Among methods using conventional observation data such as solar radiation to retrieve AOD, the algorithm developed by Qiu [1997, 1998] is particularly suitable for application to China. Qiu's method was applied to calculate 0.75-1am AOD, approximately equivalent to that of the wide band of 0.3-4.0 !.tm [Qiu, 1998]. However, as with other methods, this method was also limited to only using the direct solar radiation for cloud-free sky conditions to retrieve AOD at one moment. Because of random cloud cover it is difficult to collect the

direct solar radiation data of clear-sky conditions in a large- scale range at the same moment. In addition, as well is known, AOD has obvious daily variation. So, if this method is used to retrieve the large-scale and long-time variation of AOD, it is impossible to obtain the needed solar radiation and other corresponding data.

Here a new method is developed on the basis of Qiu's [1997,1998] algorithm, which is capable of calculating monthly mean 0.75-1am AOD. The data employed are the daily total direct solar radiation, sunshine duration, monthly mean surface pressure and vapor pressure, and total ozone amount. The retrieval of AOD follows two steps: first, eliminate the cloud effects from monthly mean direct solar radiation amount; second, weed out the attenuation of atmosphere due to Rayleigh scattering, moisture, and ozone.

The details of the iteration steps of calculating the monthly mean 0.75-!.tm AOD are as follows:

1. Suppose that Go © =1. 2. Let n =1.

-(n) 3. Calculate za ß

-(") •("-')') log(S)] . (1) 'ra = [log(R So t,, .00 -- go

4. Calculate Go (")'

-(n) -(n) Go © =( 1 + b 'co + c 'ca )f2. (2)

5. Let n=n+ 1, repeat steps 3 and 4. --tn-l)

6. When /•0 I<q, end the iteration (taking here q=0.001).

R is the ratio of solar radiation between 0.3 and 4 gm to the solar constant So, and tm is the mean molecular transmission from 0.3 to 4 gm. Different from Qiu's method, here the total direct solar radiation S used was treated as the monthly mean

LUO ET AL.: AEROSOL DISTRIBUTION AND VARIATION IN CHINA 14,503

value as

S- S,, total monthly direct radiation (J/m 2) (3) d,, total monthly sunshine duration (second)

the cosine solar zenith angle g0, was treated as monthly mean value,

g(, = g0 = (sinqosini5 + cosqocosiS)/2 (4)

In (4),

= (5)

t,,,: tm, (1- AH,.O)(1 -- •/o• )(1-- ./•lalr)fl 1 (6a)

AH20 •-• 1 0 -0 911+0 306 lOglo (U/•to)-O 0119 [lOglo (U/P-o)? (6b)

Ao, = 0.0345X/•0(1 + 2.2X/•0) +0.0218X/It0(1 + 0.042X/It 0 + 0.000323X2/[t0 (6c)

Aa,, = 0.000014 P / g o (6d)

15 fl = 1- 0.000255 x/rvx / g0 - 0.0000903 v 4rx / g,, (6e)

retrieve their yearly and monthly mean AOD from year of 1961 to 1990. For each station, X is treated as the same in every year and just varies with month, which is the 12-year averaged value of Total Ozone Mapping Spectrometer (TOMS) derived ozone data from 1979 to 1990. The empirical relationships of U and E employed for 13 stations are developed by Yang and Qiu [1996], and those for the other five stations are provided by Qiu J. (private communication, 1997), and those for the others Wang and Liu [1993]. The parameter go was actual treated simply as the half of the maximum cosine solar zenith angle of the midmonth day, [t,,. The errors caused by those treatments will discuss in section 4.

As shown in Figure 1, except for Shanxi Province, Inner Mongolia Autonomous Region, Hunan Province, Taiwan Province, and main body of Tibetan Plateau, all other provinces (autonomous regions, municipalities) have their own representative stations. The selected 46 stations mainly covers most regions of China mainland. The characteristics of each station are briefly described in Table 1. There are only -10 years of data for the 1980s at the Nanchong, Mianyang, and Mengzi stations. In the rest of 43 stations, Yinchuan has data for 25 years, Chongqing for 27 years, Changdu and Dunhuang for 28 years, and the other five stations (Tianjin, Nanjing, Hangzhou, Changchun, and Kunming), have 29 years data; all other 34 stations have 30 years of data from 1961 to 1990. Therefore all 46 stations were included in the

following patterns of yearly and monthly mean AOD distribution, but only the latter 43 stations are used to analyze the variation of AOD.

b - (0.383 - 0.93 • 0 + 0.55 • 02) (),*-2) -( 0.4- 0.67 •0 + 0.36 • 02) ( ),*- 2) 2 (7)

c = (0.89-2.1 g0 + 1.23 g 02)( •/>g- 2) + 0.006 (1 - 14.7 • 0 + 143 • 02)( ),* - 2) 2 (8)

f2=1+0.175(),*-2)(1-1.08U)•/(l+0.36U+10g03 U1/2), (9)

where U is monthly mean column efficient moisture content (cm), which was calculated by using the experimental relation to the surface vapor pressure E, P is the monthly mean surface pressure (mbar), 2' is the monthly mean total ozone amount (cm), AH:o, Ao•, and Aa,r are average absorption of water vapor, ozone, and uniformly mixed gases, respectively, (p and 8 refer to the latitude of the station and the declination, respectively, and •,* is Junge distribution parameter.

By normalizing the monthly total direct solar radiation with the monthly total sunshine duration, the cloud effects could be eliminated. The above parameterization are developed under the assumption of the Junge size distribution with •,*:2.5. According to Qiu's [1998] study, when •, =3 or 2.5 is used, the standard errors of optical depth solutions in the retrieval are all <5% for every atmospheric model. The real part of aerosol refractive index is assumed to be 1.5, while the imaginary part be a constant as 0.01 in the wavelength range <1 gm, and for the range from 1 to 4 gm, taking value of 0.01, 0.02, 0.03, .04, and 0.05, respectively.

On the basis of the improved approach above, we select 46 A class solar radiation stations over China (Figure 1) and

3. Results and Discussions

3.1. Distribution of Yearly Mean and Monthly Mean AOD Over China

Figure 2 shows the distribution of 30-year mean 0.75-•m AOD over China, which shows a typically geographic feature. To the east of 95øE, a largest center (0.69) lies in the Sichuan Basin. To the west of 95øE, the south Xinjiang Basin is another center of AOD, with the value smaller than that of Sichuan Basin. There are also other high AOD regions in the eastern part of Gansu Province, the middle reaches of Yangzi River, and coastal areas of Guangdong Province, while most parts of northeast, northwest, Yunnan Province, and south China coastal areas are of lower value.

There are three stations with AOD greater than 0.6; they are Chengdu (0.69), Chongqing (0.66), and Nanchong (0.64), which all locate in the Sichuan Basin. Of the 10 stations with

AOD between 0.45 and 0.6, four located in the south Xinjiang Basin; three in the east part of southwest China, two in the east part of northwest China; the other is Wuhan City. The smallest AOD, with a value of 0.18, is present in Jinghong station in Yunnan Province, southwest of China. Compared with other cities, the AODs in the three largest cities of China, Beijing, Tianjin, and Shanghai, belong to middle and lower levels.

Figures 3 to 9 show the distribution of 30-year mean 0.75- gm AOD for several representative months over China except for the main body of Tibetan Plateau. In January, east of 95øE, centers of AOD are located in the east part of northwest China, Sichuan Basin, and the northern Guizhou Province, with the highest value in Lanzhou (0.64) and Chongqing (0.63).

14,504 LUO ET AL.: AEROSOL DISTRIBUTION AND VARIATION IN CH1NA

Table 1. Features of 46 Stations in China a ,,

No. Station Altitude, m Topography Population Land Use AOD

1 Aletai 735.1

2 Kashi 1289

3 Hetian 1374.6

4 Kuche 1072.5

5 Urumchi 178.5

6 Reqiang 122.3 7 Hami 737.9

8 Dunhuang 1138.7 9 Xining 2261.2 10 Lanzhou 1517.2

11 Yinchuan 1111.5

12 Xian 396.9

13 Taiyuan 783.7 14 Beijing 29.2 15 Tianjin 3.3 16 Shenyang 41.6 17 Changchun 236.8 18 Haerbin 1071.2

19 Jiamusi 81.2

20 Zhengzhou 109 21 Jinan 51.6

22 Yantai 46.7

23 Changdu 3175.4 24 Chengdu 505.9 25 Mianyang 1300.7 26 Nanchong 46.7 27 Chongqing 241.9 28 Yichang 69.7 29 Wuhan 22.8

30 Hefei 23.6

31 Nanjing 8.9 32 Hangzhou 7.2 33 Shanghai 4.5 34 Jinghong 533 35 Kunming 1891.3 36 Mengzi 1243.3 37 Zunyi 849.3 38 Guiyang 1071.2 39 Nanning 122.3 40 Haikou 17.6

42 Nanchang 46.7 43 Ganzhou 124.8

44 Guangzhou 6.3 44 Guilin 166.7

45 S hantou 1.3

valley Gobi

Gobi, oasis

valley

plain, hill desert

Gobi, oasis

desert, oasis valley

valley

plain plain plain plain plain plain plain plain plain plain plain

foothill

valley basin

basin

basin

mountain

mountain

plain plain

plain plain plain

mountain

plain hill

valley

valley hill

plain, coast plain valley delta

karst

coast, plain

210,302 agriculture, stock breeding 0.34 311,141 agriculture, stock breeding 0.51 154,352 agriculture, stock breeding 0.53 368,440 agriculture, stock breeding 0.48 1,391,896 industry 0.4 28,652 agriculture, stock breeding 0.56 352,929 agriculture, stock breeding 0.42 129,902 agriculture 0.42 711,264 industry 0.48 1,749,752 heavy industry 0.55 586,022 industry 0.42

3,130,064 industry 0.43 2,233,221 industry 0.41 8,130,686 industry 0.39 6,006,145 industry 0.37 4,799,851 industry 0.39 2,826,890 industry 0.39 2,991,608 industry 0.33 809,299 industry 0.38

2,039,286 industry 0.41 2,574,930 industry 0.42 1,567,745 agriculture 0.38 85,916 agriculture, stock breeding 0.45

3,259,847 industry 0.69 1,017,498 light industry 0.43 1,781,730 industry 0.64 6,714,756 industry 0.66 595,812 light industry 0.44

5,302,373 industry 0.5 1,279,420 light industry 0.42 2,763,560 industry 0.36 1,718,887 light industry 0.4 10,706,191 industry 0.37 363,111 agriculture 0.18 1,730,621 light industry 0.43 306,267 agriculture 0.37

1,427,689 light industry 0.5 2,238,354 industry 0.49 1,308,062 light industry 0.38 527,899 light industry 0.34

1,621,049 light industry 0.32 444,830 light industry 0.35

3,993,008 industry 0.45 611,247 light industry 0.37 1,113,200 light industry 0.31

46 Fuzhou 88.4 hill 1,436,878 light ind•..s•x.. ............ 0.3

a Cited from Chinese statistic Press [1998]. The population shown is the population of the city where the station is located. The population of each station is followed by a brief description of the area surrounding of each station. Most cities embracing the station have changed significantly from 1961 to 1990, especially in the latter decade with implementation of the reform and open policies. For instant, a small town like Haikou in 1970 has become a medium sized city in 1990, and as consequence, the emission sources changed. Thus here just the common impression for 1990s is given.

LUO ET AL.: AEROSOL DISTRIBUTION AND VARIATION IN CHINA 14,505

50N Yearly avejaged

40N•

20N- 8(•E 9•)E 10•E 11'•E 120E 130E 140E

0.70

0.65

0.60

0.55

O.5O

0.45 : 0.40 ...

..... 0.35

0.30

50N-

4o N-

30N-

2ON'

Feb. or.. ......... _

.... ß '.'""':"•C•'•' '"'•. -'-• 80E 90E 100E 110E 120E 130E 14•

I '70 0.65 0.60 0.55

'•0 50 •;•:" '•': '"• 0.45

•'• "•-• 0.40

..... 0.35

0.30

Figure 2. Distribution ofmultiyear mean (1961-1990) AOD over China.

Figure 4. Distribution of multiyear mean (1961-1990) AOD for February over China.

Additionally, AOD in the middle reaches of the Yangzi River around Wuhan City is also relatively higher than surrounding areas. For the area west of 95øE, the south Xinjiang Basin is another higher-level region. Table 2 lists the frequency numbers of AOD for each month. It indicates that all eight stations with the A OD larger than 0.5 are lying in the eastern part of northwest China, Sichuan Basin, and the middle reaches of the Yangzi River. Supposing the China mainland is divided into two parts at 95øE, i.e., eastern and the western, in January the A OD in the eastern part is larger than that in the western part.

The AOD distribution in February, is similar to that in January. The eastern large center is located in the eastern part of northwest China, Sichuan Basin, and north Guizhou, as well as the valley between the Han and the Yangzi River, while the western large center is located in the southern Xinjiang Basin. AOD increases over almost all the China mainland. Compared with January, the number of stations with AOD larger than 0.6 increases from 2 to 5 (stations Lanzhou (0.69), Chongqing (0.69), Chengdu (0.68), Zunyi (0.64) and Wuhan (0.64), respectively). The AOD value in eastern center is larger than the value in the western center.

In March and April, AOD increased over almost all the China mainland. However, the enhancement varied with regions, and AOD distribution is somewhat different from the preceding 2 months. From west to 95øE, AOD increases rapidly from the southern Xinjiang Basin to the western part

of the Hexi Corridor. It is obvious that the enhancement of

AOD in the western center is stronger than that in the eastern center. Nevertheless, in the eastern center, the Sichuan Basin and the eastern part of northwest China are still the larger- value center.

More than two thirds of the total 46 stations have AOD

larger than 0.5. Among them, there are nine stations in March and seven stations in April with AOD larger than 0.7, which mostly lie in Sichuan Basin and southern Xinjiang Basin. The highest values of March (0.81) and April (0.89) both appear at Reqiang station, which is located in the eastern part of the southern Xinjiang Basin. Except for a few big cities, AOD decreases from west to east in north China. This may be caused by the frequent duststorms in this region in spring season, and the gradient of AOD may implicate the routine of the sand transportation. It worth noting that the middle reaches of Yangzi River are another relatively larger-value area and the AOD in south China coastal regions also increases rapidly.

A OD in May appears a decreasing tendency for most areas compared to March and April, except for a few stations such as Chongqing. The stations with A OD larger than 0.5 have decreased obviously, with the most distinct reduction occurring in the east part of northwest China. There are only four stations with AOD greater than 0.7, which are Chongqing (0.83), Chengdu (0.77), Nanchong (0.70), and Reqiang (0.77). The Sichuan and the south Xinjiang Basins remain the large-

0.70

.

0.65

.

ß 0.60

•• 0.55 .,,:•.•?•! o. 5 o

0.45

•:' 0.40

0.35

0.30

Figure 3. Distribution ofmultiyear mean (1961-1990) AOD for January over China.

t30E 140E

0.90

0.85

ß .. 0.80 ." . ': ß-0.75

..½•½•,• 0.70

'½g• 0,65 :' 0.60

0.55

0 5O

O.45

0.40

Figure 5. Distribution of multiyear mean (1961-1990) AOD for April over China.

14,506 LUO ET AL.: AEROSOL DISTRIBUTION AND VARIATION IN CHINA

0.70

0.65

0.60

-.•: 0.55

0.50 •04 ....... •....____•.• . 5 '•"•'"'"'" 0.40

• 0.35

• 0.30

0.25

0.20

Figure 6. Distribution of multiyear mean (1961-1990) AOD for May over China.

Figure 8. Distribution ofmultiyear mean (1961-1990) AOD for October over China.

value centers. However, AOD is smaller in the eastem part of China, especially in the coastal southeast China and the Yunnan Province.

In June, AOD keep on decreasing in comparison with spring season. The most significant reduction occurs in the western part of China; for example, AOD of Reqiang falls from 0.77 in May to 0.57 in June. There are only six stations with AOD above 0.5, and three stations with AOD above 0.6, Chengdu (0.76), Chongqing (0.74), and Nanchong (0.71), all lying in Sichuan Basin. Except for Sichuan and south Xinjiang Basins, AOD is less than 0.45 in most areas of China.

From July to October the distribution of AOD appears a typical geographical feature. Sichuan Basin and south Xinjiang Basin are two large-value centers, and AOD decreases from the centers to surrounding areas. In July and August, there are only four stations with AOD larger than 0.5, of which three lie in Sichuan Basin and the other lies in south Xinjiang Basin. In September and October, there are only three stations with a value larger than 0.5, and all are located in S•chuan Basin. Additionally, around coastal region of Guangdong Province, AOD is also relatively larger. While in other areas of China, AOD is relatively small. The 0.40 isopleth covers most regions of China except the Sichuan and south Xinjiang Basins. However, AOD is very small in the area south to middle and lower reaches of Yangzi River; for instance, in Jinghong, Fuzhou, and Haikou it is only •<0.2.

West to 95øE, AOD decreases dramatically in November and December with a value below 0.35 in most stations of this

area. The large center of south Xinjiang Basin, which used to be one of the larger-value centers of AOD in most months, now disappears. East to 95øE, AOD decreases to below 0.6 over Sichuan Basin. More than 76% stations have the AOD

between 0.3 and 0.5, and the differences between regions become smaller than before. Beside the Sichuan Basin, the eastern part of northwest China becomes the second larger- value center. While AOD in middle and lower reaches of the

Yangzi River appears to slightly increase, and it remains smaller in most part of northeast and northwest China, along with Yunnan Province and south China coastal regions.

Generally speaking, AOD distribution for each month is similar to that of the annual mean pattern, implying "basin" effect is very significant. From November to January, west to 95øE, AOD is quite small in most parts of northwest China. While the large-value center is located in Sichuan Basin and eastern part of northwest China east to 95øE. AOD is also relatively larger in the middle reaches of Yangzi River, and it is smaller in most parts of northeast China, Yunnan Province, and coastal south China during the winter season. From June to October, AOD distribution appears to be a typical geographic feature; that is, the Sichuan Basin and the south Xinjiang Basin are two larger-value centers. While AOD is relatively smaller in the rest regions with the smallest value

50N- Jut. ":::.:• .... 0.65 •.•: . ....•" •!•.. "•

•...••? ..-:•' ' :• • •--•...• .... ' ..... ?..:• •-::;•. ...... ..- o. s s

•0.45

30N- •0.35

20N , ............ 'i' .................. ". .............. , .......... • ....... 0.25 80E 90E 100E 110E 120E 130E t40E

Figure 7. Distribution of multiyear mean (1961-1990) AOD for July over China.

50N'

4ON'

30N'

20N •

80E 90E 100E 110E 120E 130E 140E

0.70

0.65

0.60

: .0.55 ...

•0.50 • 0.45 '•':• o.4o •..../..:•-..•

•0.35 0,30

0.25

0.20

Figure 9. Distribution ofmultiyear mean (1961-1990) AOD for November over China.

LUO ET AL.' AEROSOL DISTRIBUTION AND VARIATION IN CHINA 14,507

Table 2. Frequency Numbers of AOD of 46 Stations by Month

AOD Jan. Feb. March April May June July Aug. Sept. Oct. Nov. Dec. Average

>0.8 1 1 1

0.7-0.8 8 6 3 3 2 I 1

0.6-0.7 2 5 9 7 2 0 I 2 2 3 3

0.5-0.6 6 12 12 17 11 3 I I 0 0 4 3 5

0.4-0.5 16 20 15 13 19 14 7 4 12 11 9 10 19

0.3-0.4 19 8 1 2 8 21'-' 17 18 19 23 26 28 17

0.2-0.3 2 I I 5 14 18 11 8 6 4 1

< 0.2 1 I 4 2 1 1 1 1 1

present in southeast coastal areas. From February to May, the eastern part of northwest China becomes another larger-value center besides the Sichuan and south Xinjiang Basins. AOD is apparently larger in most of other regions in spring season, and the most dramatic enhancement of AOD occurs in

northwest China. As to the reason why the larger AOD always occurs in the Sichuan and south Xinjiang Basins. First, the special basin topography may weaken surface wind, stabilize stratification, and then halt pollutant transportation. Second, Sichuan Basin was also known as the high SO2 concentration and the high humidity in China, and the high humidity is very favorable for the transformation of SO2 to sulfate particles. Embracing the largest desert of China, the Takelamagan desert, south Xinjiang Basin is the main source of mineral aerosol in China.

3.2. Distribution of AOD for Three Decades Over China

Figure 10 shows AOD distribution of the 1960s over China mainland. It can be seen that AOD distribution particularly appears to be a geographical feature. That means two larger- value centers located in two basins, with the largest value in Sichuan Basin followed by the south Xinjiang Basin. However, in the eastern part of China, A OD is relatively smaller, especially in southeast China coastal areas.

In the 1970s, AOD distribution remains the typical geographical feature. Compared with the 1960s, it shows an increasing trend in most regions of China except the western part of the Xinjiang Autonomous Region, Yunnan Province, and some parts of Guangxi Province. The most obvious enhancement of AOD occurs in Sichuan Basin, middle and lower reaches of Yangzi River, and south China coastal regions as well (see Figure 11).

During the 1980s, AOD keeps on increasing over almost whole China regions except for a few individual areas. Figure 12 shows the difference between the 1980s and 1960s. It

indicates that the significant increasing occurs over whole eastern part of China. Among the increasing areas, the most dramatically enhancement occurs over the northern part of Guizhou Province and the whole middle and lower reaches of

the Yangzi River, with the largest increment up to 0.21. So, a large change occured in the A OD distribution. This means that a new large-value center, namely, the third one following the Sichuan and south Xinjiang Basins, had been formed in the middle and lower reaches of the Yangzi River. (For more details for the 1980s, see Luo et al. [2000b]. )

3.3. Variation Characteristics of AOD Over China

in the Last 30 Years

Among the 46 stations, only Nanchong, Mianyang, and Mengzi have nearly 10 years of data for the 1980s. For the remaining 43 stations, all of which have data for longer than 28 years except for Yinchuan and Chongqing, the linear trend of A OD through the time series of the monthly mean from 1961 to 1990 is calculated (Yinchuan has 295; Chonhqing has 316; the rest are all over 330). Then the yearly mean variability of AOD, A%, is obtained by converting the value of the linear trend from per month to per year.

Figure 13 shows the linear trend of AOD over China except Tibetan Plateau in the last 30 years from 1961 to 1990. It can be seen that the most dramatically increasing linear trend occurs in the middle and lower reaches of the Yangzi River, eastern part of the Sichuan Basin, and the northern part of Guizhou Province. The highest value (0.011 yr -•) happened in

50N-

40N-

30N-

20N-

I i I I I !

•d•. r' ' 0.65 o.60

..... o.ss 4øN- :T

• " •"•] 0.45 30N- 0.4o

0.30

0 2s 8•E 9•E • 00E • • 0E • 20• • 30E • 40E 8•E ' ...................... 90E 100E 1 I•E •2•E 130E 140E

Figure 10. Distribution of AOD for 1960s over China.

0.15

012 ß

ß

...

..

:,,:.,,....•i 0 09 ;0 06

0.03

Figure 11. The difference of AOD between 1970s and 1960s over China.

14,508 LUO ET AL.: AEROSOL DISTRIBUTION AND VARIATION IN CHINA

50N-

40N-

30N-

2ON-

'0.24

.... ß . '0,21

-•0,18 0.15

0.12

0.09

0.06

0.03

•,½ 0.00 .,,•-0.03

,•-0.06 Figure 12. The difference of AOD between 1980s and 1960s over China.

the middle reaches of the Yangzi River, implying the most -obvious increase there. The linear trend is also fairly large in the eastern part of Qinghai Province, the coastal areas of Guangdong Province, southern part of north China, and the western part of Shandong Peninsula.

However, AOD increased just slightly over most parts of northeast China and northwest China. Note that over western part of Xinjiang Autonomous Region and some part of Yunnan Province, AOD appears as a decreasing trend. In fact, in north China, soil and sands are the major sources of aerosols. Yang [1998] found that the frequency of sandstorm has reduced since the 1980s in north China. This may explain the slightly increasing and even decreasing trend of AOD in north China.

Table 3 lists the mean AOD averaged at the all stations. It also manifests that the increase of AOD in the last 30 years is significant. Compared to the 1960s, the mean value increases 9.5% in 1970s and 21.8% in 1980s.

Figure 14 shows the yearly mean AOD variation curve for the 44 stations, from which it can be found that the AOD shows a clearly increasing tendency from 1961 to 1990. The curve generally can be divided into two periods: (1) from 1961 to 1975, AOD is smaller than the 30-years mean value; and (2) from 1976 to 1990; it is higher than the 30-year mean valu•e. A similar peak in 1982 and 1983 is found by Qiu [1997] and was attributed to the volcanic activity. Here we also thought that the AOD peak in 1982 or 1983 in this paper may

Table 3. Value of Averaged AOD of 46 Stations for Three Decades

Average Standard Minimum Station Maximum Station Deviation

1960s 0.381 0.095 0.17 Jinghong 0.65 Chengdu 1970s 0.417 0.098 0.15 Jinghong 0.74 Chongqing 1980s 0.464 0.104 0.21 Jinghong 0.79 Chengdu

Averathe 0.423

partly be caused by the eruptions of El Chichon volcano and the downward trend from 1982 to 1990 might be partly explained by AOD returning to pre-EI Chichon levels to some degree. Figure 15 shows the 30-year mean AOD variation of the 44 stations for each month. Generally, the variations of AOD with years by month show significant increasing trend. From early 1960s to early 1980s, AOD increased with fluctuation but continuously for most months. However, in the mid-1980s, AOD shows a short-period decrease for most months. During the later 1980s, the trend is difficult to distinguish. For example, in several months, such as January, February, April, and May, AOD increased continuously, while in other months, e.g., March, June, July, August, October, and November, AOD shows a decreasing trend. Table 4 lists the 44 stations multiyear averaged AOD by month, their linear trend, and linear regressive correlation coefficient for 30 years from 1961 to 1990.

1. On average, AOD over China is larger in spring and smaller in summer. The ratio of the maximum (April) to the minimum (August) is 1.7. The standard deviation of AOD is also higher in spring with the maximum in April and smaller in winter with the minimum in December.

2. The minimum of the multiyear mean AOD for each month generally appears in the early 1960s, while the maximum generally appears in the early 1980s. During the 30 years, the smallest value (0.24) occurs in August 1966, and the largest one (0.70) occurs in March 1985.

3. In the last 30 years, AOD for each month shows a significant increasing trend with all the linear regression correlation coefficient larger than 0.6. The higher linear trend presents in spring with the maximum of 0.60 per century in March, while the smaller occurs in winter with the minimum of 0.29 per century in December. The linear trend in summer is similar to that in autumn.

50N-

4ON'

3ON'

20N

8!•E

• "••....•--.• "-• 0.012 • . .0.010

•:! 0.008 ?'•-;• • 0.004

••, ..,,;;•• .••• ........... o. oo• 0.000

• t ' " -0.004

130E 140E 9(•E ..... 1%E 11b E i2J3E

Figure 13. mainland.

The linear trend (yr -•) of AOD over China

0.55

-= 0.50

'• 0.45 .,•

.• 0.40

.• 0.35

0.30

1960 1965 1970 1975 1980 1985 1990

Figure 14. Yearly mean AOD variation curve of 44 stations averaged from 1961 to 1990. ( The broken line shows the three-years running average. )

LUO ET AL.' AEROSOL DISTRIBUTION AND VARIATION IN CHINA 14,509

0.8

0.2

0

1961

Jan. •Feb. ' ' 'Mar. -- Apr. ,

i [ [ [ i [ • [ i ! i i ! ! ! ! , , ! i i i ! i [ [ i ,

1965 1969 1973 1977 1981 1985 1989

0.8

• 0.6

..•

• 0.4

• 0.2

o

1961

I ---- May • Jun. ' ' 'Jul. -- Aug.

b

1965 1969 1973 1977 1981 1985 1989

0.6

-"- Sep. • Oct. ' ' 'Nov. -- Dec.

-• 0.4

..•

• 0.2

1961 1965 1969 1973 1977 1981 1985 1989

Figure 15. Yearly mean AOD of 44 stations averaged for each month: (a) January, April, July, October, (b) February, May, August, November, and (c) March, June, September, December.

4. Validation of the Results and Uncertainties

4.1. Error Analysis

4.1.1. Error effect of $m, dm, and S. According to (1) and (3) the error of AOD caused by an error in monthly total direct solar radiation (&,)and total sunshine duration (d,,) is

A-r(,--[t0( 1 Ad,,,-1--•-•S,,). (10) at,,,

Because Sm is in positive correlation with rim, Atm and AS,,, are assumed to be of the same sign. Supposing Atm and ilS,,, are both within +2%, the solution error will within +_0.02, 50.01, and +_0.006 for [t0:l, 0.5, and 0.3, respectively.

The treatment of S in this paper may result in obvious errors for retrieving monthly mean AOD if the cloud cover over a certain station has some preponderant probability in a period during a day or a month. Unfortunately, we have not found the results about the daily or monthly cloud cover variation characteristics of 46 selected stations. Hence we

assumed that for a long time period such as 30 years, the cloud cover was thought to be random. So the estimate of monthly mean AOD was expected to be unbiased in this paper.

4.1.2 Error effect of it,,. In order to analyze the sensitivity of AOD respond to g,, we choose four representative stations on the basis of their location, Jiamusi (46.49øN), Beijing (39.56øN), Hangzhou (30.14øN), and Guangzhou (23.08øN) and calculate their multiyear mean AOD response with the 5% increase of g(, for 4 months. Table 5 indicates that the extent of AOD response to P0 is a t•ctor of 2 in general and even larger than a factor of 3 in some case. Therefore it is absolutely necessarily to compare the simplified monthly mean cosine solar zenith angle used in this paper with the real monthly averaged solar zenith angle !a

As a definition, cosine solar zenith angle !a is

cos !3 - sin q) sin 6 + cos q) cos 6 cos •, (11)

where ( is the solar hour angle, and (p and 15 are as the same as in equation (4). The monthly mean cosine solar zenith angle,

Table 4. Yearly Averaged AOD Value, Their Liner Trend, and Linear Regression Correlation Coefficient (LRCC) for 44 Stations Averaged a

Average Standard Minimum Maximum Liner Trend LRCC Deviation

Value Year Value Year

Jan. 0.41 3.56E-2 0.34

Feb. 0.49 6.02E-2 0.38

March 0.57 6.37E-2 0.45

April 0.57 6.53E-2 0.41 May 0.48 4.70E-2 0.40 June 0.41 4.55E-2 0.33

July 0.34 4.80E-2 0.27 Aug. 0.34 5.10E-2 0.24

Sept. 0.37 4.48E-2 0.29 Oct. 0.3 7 3.62E-2 0.31

Nov. 0.37 3.73E-2 0.30

Dec. 0.37 3.18E-2 0.30

Yearly mean 0.43 4.00E-2 0.35 Read 3.56E-2 as 3.56x10 -2.

1961 0.47

1961 0.60

1961 0.70

1961 0.69

1964 0.57

1961 0.53

1971 0.46

1966 0.43

1966 0.50

1969 0.44

1961 0.45

1961 0.43

1961 0.50

1990 0.35E-02 0.85

1984 0.53E-02 0.77

1985 0.60E-02 0.83

1983 0.49E-02 0.66

1979 0.40E-02 0.74

1982 0.32E-02 0.61

1982 0.43E-02 0.80

1988 0.49E-02 0.84

1982 0.38E-02 0.75

1982 0.33E-02 0.79

1982 0.33E-02 0.78

1982 0.29E-02 0.80

1982 0.41E-02 0.90

14,510 LUO ET AL.' AEROSOL DISTRIBUTION AND VARIATION IN CHINA

Table 5. Response of Multiyear Averaged AOD to 5% Increase of

Table 7. Multiyear Averaged AOD for Different Treatment of Monthly Mean Cosine Solar Zenith Angle a

Station Jan. April July Oct.

Jiamusi 7% 10% 12% 9%

Beijing 8% 1 aø/- 13% 10% Hangzhou 10% 10% 16% 11% Guan•zhou 10% 11% 12% 12%

g m, was calculated here by integrating the • day after day with a 0.1 ø interval during sunrise and sunset in a day.

As a result, Table 6 indicates that g m is larger than The increment ranges from 22% to 32% for these representative cases, varying with stations and seasons. The difference is generally larger in high latitude than in lower latitude.

Table 7 lists the AOD calculated with three different

monthly mean cosine solar zenith angles. It is apparent that AOD calculated with g m, or g mm (mean cosine solar zenith in the midday of a month) is larger than that calculated with g0 in this paper. The difference extent is between 50% and 86%, and the change seems to obey no obvious rule with different season and latitude.

In fact, the total solar radiation in a day contains a radiation amount in every sunshine hour, but the contribution at different solar hour angle during a day and a month is much different. So even if using g m represents equivalent monthly mean solar zenith angle, we think it still seems not yet perfect to describe the truth and should do more study in the future. Nevertheless, the uncertainty of AOD caused by [t0 in this paper is evident. Details of error analysis of aerosol size distribution, water vapor amount, and ozone amount are given by Qiu [1998].

4.2. Comparison With Other Results

Qiu [1997] had calculated the 0.75-gm AOD for 10 stations over China from 1980 to 1994; nine of them are also calculated in this paper. As shown in Figure 16, both results of time series of AOD from 1980 to 1990 show good agreement in trend. As to the yearly mean value (see Table 8), both results of Beijing, Zhengzhou, Shanghai, and Guangzhou are almost consistent; the other stations in this paper are larger to a different extent than those of Qiu's, especially for Kashi, Urumchi, and Kunming. Qiu's result was calculated by using

Table 6. Comparison of [to and [t m

Station Parameter Jan. April July Oct.

Jiamusi [to 0.19 0.40 0.45 0.28 [tm 0.25 0.50 0.56 0.37 increment 32% 25% 22% 30%

Beijing go 0.24 0.43 0.47 0.33 gm 0.32 0.54 0.59 0.43 increment 31% 25% 24% 29%

Hangzhou go 0.31 0.47 0.49 0.39 gm 0.41 0.59 0.62 0.50

increment 30% 26% 25% 29%

Guangzhou [to 0.36 0.49 0.50 0.42 [tm 0.46 0.62 0.63 0.54 increment 29% 26% 26% 28%

Station Jan. April July Oct. Yearly Mean

Jiamusi

Beijing

Hangzhou

Guangzhou

x 0.32 0.54 0.34 0.35 0.38

'17 m 0.50 0.81 0.54 0.58 0.59

'lJmm 0.50 0.81 0.54 0.58 0.59

(Xm-X)/X 56% 50% 59% 66% 55% • 0.38 0.52 0.3 0.35 0.39

'1; m 0.62 0.78 0.51 0.59 0.61

'lJmm 0.59 0.81 0.51 0.59 0.61

(Xm-X)/X 63% 50% 70% 69% 56% • 0.42 0.54 0.22 0.34 0.40

'1; m 0.71 0.81 0.41 0.57 0.66

'lJmm 0.68 0.81 0.41 0.57 0.66

(Xm-X)/X 69% 50% 86% 68% 65% • 0.41 0.66 0.42 0.29 0.45

•:m 0.66 1.02 0.69 0.51 0.72

'[mm 0.66 1.0 0.69 0.53 0.72

{•:m-Q/•: 61% 55% 64% 76% 60%

a l;, AOD caculated by using siplifted monthly mean cosine solar zenith angle [to as in this paper; x .... AOD caculated by using real monthly mean cosine solar zenith angle [t,,,; x ...... AOD caculated by using the daily mean cosine solar zenith angle of the midday in a month.

the clear-sky direct solar radiation at 1400 LT. According to the analysis of daily variation of atmospheric transparency over China [Wang and Pan, 1982], west to 95øE, atmospheric transparency reaches its peak at noon. This means the AOD that Qiu obtained in the area west to 95øE is the minimum in a day. In this paper we employ the monthly mean direct solar radiation and sunshine duration data and so on, which include the information of every sunshine times during a day, and therefore our results present the real averaged situation of AOD. So it is reasonable that our result is somewhat larger than Qiu's for Kashi and Urumchi, which are located west of 95øE. However, it is hard to explain the discrepancy at Kunming station. Generally, our results are almost in good agreement with those of Qiu's, i.e., the maximum AOD both in Wuhan, and the minimum both in Kunming.

Using the clear-sky surface visibility data of 70 stations of China at 0800 and 1400 LT in 1980, Zhao et al. [1986] analyzed the transparency distribution for five wavelengths, 0.4-0.8 [tm at 0.1-[tm intervals. Both the patterns of distribution and the seasonal variation of their transparency are broadly consistent with those results in this paper. By interpreting their 0.7-•tm wavelength transparency into the AOD at the same wave band, it was found that the AOD ranges from 0.36 to 0.51 over the Sichuan Basin and the valley between Han River and Yangzi River and from 0.23 to 0.36 for most areas of China. In this paper, there are six stations located in S ichuan Basin and the valley between Han River and Yangzi River. Except for Chongqing with higher AOD value, the results of other stations are in good agreement for both cases. However, for the rest of the areas of China, the magnitudes of AOD in this paper are slightly larger than those results of Zhao et al.'s. The discrepancy is due to different stations chosen in Zhao et al.'s work and this paper. In China, solar radiation stations have a limited number and are most

located in cities, while most conventional meteorological

LUO ET AL.' AEROSOL DISTRIBUTION AND VARIATION IN CHINA 14,511

0.8

...... iu) .... 0.6

0.4

0.2

0

0.8

0.6

O4

O2

0

0.8

0.6

O4

O2

0

1980 1982 1984 1986 1988 1990 1980 1982 1984 1986 1988 1990 1980 1982 1984 1986 1988 1990

0.8 0.8 0.8

0.6 0.6 - - -• - '---'- ......... 0.6

0.4 0.4 --•' 0.4

02 02

0 0 0

1980 1982 1984 1986 1988 1990 1980 1982 1984 1986 1988 1990 1980 1982 1984 1986 1988 1990

0.8

O6

O4

0.2

0

' ' ' Zhengzhou(•_•_U•_ "ø-•Zhengzhou(Luo) 0.8

O6

O4

0.2

0

08

06

04

0.2

0

'ø 'Urumchi(Qiu) -ø"Urumchi(Luo)

1980 1982 1984 1986 1988 1990 1980 1982 1984 1986 1988 1990 1980 1982 1984 1986 1988 1990

Figure 16. The comparison of AOD of nine stations calculated by Qiu and this paper from 1980 to 1990.

observation station are located in small cities or county seat. Thus that our results are lightly larger than Zhao et al.'s seems reasonable.

In 1983, Mao et al. [1983] calculated the AOD in Beijing at six different wavelengths using the direct solar radiation data of 115 clear days in forenoons from July 1980 to July 1981. Figure 17 shows their result and ours for the same year. It can be seen that the monthly variation curve shows a good agreement in tendency, but our result is obviously larger. According to Mao et al. [1983], AOD of Beijing varies dramatically with the range of +0.1 to +0.3 in a day, sometimes even up to 0.5. The observation period chosen by Mao et al. is forenoon when AOD is the minimum in a day. Considering our calculated AOD is the mean value for the whole day, it also seems is acceptable that our result is larger than Mao et al.'s.

In comparison with observational data or results calculated by other scientists in certain period, it is clear that the results of this paper are mainly reliable. In fact, because of the mismatch in measurement time and the quite large daily variation, it is difficult to strictly compare two results under the same conditions. Nevertheless, owing to uncertainties of the monthly mean cosine solar zenith angle and other factors, our retrieved AOD still have some problems. This needs to be checked by using plenty of powerful real data in the future, and we also need to urgently develop much advanced retrieval scheme. On the other hand, because most of the stations that we used are located in the big cities, it is thus biased that

using these cities' AOD value to describe the AOD distribution for the whole China mainland. Nevertheless, the geographical distribution of AOD and its variation of China for decades in this paper are still valuable, and these results are the information that was considered very important for studying environment and climate change but have not been known yet.

5. Conclusion

With a new method improved from Qiu's, the annual and monthly mean aerosol optical depth (AOD) at 0.75 gm were retrieved by using the daily direct solar radiation, sunshine duration, surface pressure, and vapor pressure data of the 46 solar radiation stations from 1961 to 1990, as well as the TOMS version 7 ozone data from 1979 to 1990. Then the

distribution of AOD over China and its variation in the last 30

years were analyzed. Comparing our results with some observational data or results calculated by other scientists for certain sites and period, it is clear that the results here are mainly reliable, especially the geographic distribution of AOD and its variation for the last 30 years. The principal conclusions of the present analysis are as follows:

The multi year mean AOD distribution over China typically has geographical features. To the east of 95øE, the largest center of AOD (0.69) is located in the Sichuan Basin. West of 95øE, the south Xinjiang Basin is another larger center of AOD, but the value there is smaller than that in the Sichuan

Table 8. Mean Value of AOD for 1980-1990 for Stations Calculated by Qiu and This Paper

Beijing Shengyang Urumchi Kashi Zhengzhou Wuhan Shanghai Kunming Guangzhou Geermu Qiu [1997] 0.38 0.33 0.30 0.28 0.42 0.53 0.41 0.24 0.44 This paper 0.44 0.43 0.45 0.52 0.43 0.62 0.43 0.37 0.46

0.16

14,512 LUO ET AL.: AEROSOL DISTRIBUTION AND VARIATION IN CHINA

0.8

0.6

0.2

0 •

7 8

Figure 17.

- - ß Mao '-'-- !uo

9 10 11 12 1 2 3 4 5 6

Month

The comparison of 0.75-•m AOD from this paper and Mao et al.'s results for period July 1980 to July 1981.

Basin in eastern China. Following the high AOD regions, AODs are relatively larger in the eastern part of northwest China, the middle reach of Yangzi River, and Guangdong coastal areas. AOD distribution for each month is similar to

that of the annual mean pattern in that "basin" effect is very significant, but the month-to-month differences are also obvious.

In spring, besides the Sichuan and south Xinjiang Basins, AOD in the east part of northwest China is also a higher-value center. Meanwhile, most areas of the China mainland have their maximum of AOD, especially in northwest China. From June to October, AOD distribution still has their largest center located in Sichuan and south Xinjiang Basins. Additionally, around the middle reaches of the Yangzi River and Guangdong coastal area, AOD is also relatively larger. However, the rest are relative lower, among them southeast coastal areas is the lowest-value areas of AOD.

From November to the next January, AOD decreases in most areas of west to 95øE, and the larger center of the south Xinjiang Basin disappeared. Instead, two higher-value centers are all located in east of 95 ø E, i.e., the Sichuan Basin and Lanzhou City, respectively. In the areas around the middle reaches of Yangzi River, AOD is still relatively larger. Generally, in most areas of China the maximum of AOD occurs in spring, but the season in which the minimum happened varies with regions.

AOD distribution in 1960s appears a typically geographical feature over China mainland. Two larger-value centers lie in the Sichuan and south Xinjiang Basins and decrease to surrounding areas. In 1970s, AOD distribution continually remains the typically geographical feature. Except for the western part of Xinjiang Autonomous Region, Yunnan Province, and some parts of Guangxi Province, AOD shows an increasing tendency in most regions of China by compared with 1960s. The most obvious enhancement of AOD presents over the Sichuan Basin, the middle and lower reaches of Yangzi River and south coastal China. In 1980s, AOD keeps on increasing tendency over almost whole China mainland. It is worth to note that AOD increases remarkably over the eastern part of China, and the most dramatic enhancement occurs in the north part of Guizhou Province and the whole middle and lower reaches of Yangzi River, with the largest increment up to 0.21. Thus the patterns of AOD in 1980s have some obvious changes compared with those of two decades before. That means the middle and lower reaches of Yangzi River becomes the third larger-value center besides the Sichuan and south Xinjiang Basins.

From 1961 to 1990 the mean AOD of the 46 stations shows

an obvious increasing trend over China. The variation can be briefly divided into two periods, one is from 1961 to 1975 when AOD is smaller than the 30 years mean value, and the other is from 1976 to 1990 when AOD is higher than the 30 years mean value. The peak in 1982 or 1983 may partly caused by the eruptions of EI Chichon. In the last 30 years the larger linear trend of 46 stations averaged AOD appears in spring with the maximum of 0.49 per century occurred in March, and the smaller trend does in winter with the minimum of 0.29 per century occurred in December. There are three stations with the AOD more than 0.6, which are Chengdu (0.69), Chongqing (0.66), and Nanchong (0.64). All three station lie in the Sichuan Basin. Compared with other cities, AOD of Beijing, Tianjin, and Shanghai belong to the middle and lower level. During the period from 1961 to 1990, AOD increased most significantly in eastern part of the Sichuan Basin, northern part of Guizhou Province, middle and lower reaches of Yangzi River. There shows a fairly large increasing in north China, Shandong Peninsula, eastern part of Qinghai Province, and coastal area of Guangdong Province. However, the AOD increased slightly in most parts of northeast and northwest China. Specially, in western part of Xinjiang Autonomous Region and some parts of Yunnan Province, AOD appears to be a decreasing trend.

Acknowledgments. This work was supported by National Natural Science Foundation of China Major Programs No.49794030 and No. 49899270.

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He Q., Agrometeorology Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China. (hqami•hotmail.com)

Li W. and Zhou X., Chinese Academy of Meteorological Sciences, Beijing 100081, China.

Lu D., Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China.

Luo Y., Department of Earth Science, National Natural Science Foundation of China, 83 Shuangqing Road, Haidian,Beijing 100085, China. (luoyf•mail.nsfc. gov. cn)

(Received February 28, 2000; revised December 19, 2000; accepted January 3,2001.)