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15-28 Number of Civil Vehicles Owned
       
Trucks (10 000 units)
  Year
  Region
Passenger
Large
Medium
Small
Minicar
Trucks
Heavy
Middle
Light
Mini
Others
Number of
Automobile
Total
Vehicles
10 000
Motor Drivers
Drivers
(10 000 units)
(10 000 units)
(10 000 units)
units
(10 000 persons)
                             
  
  1978
135.84
25.90
100.17
192.45
  1980
178.29
35.08
129.90
245.23
  1985
321.12
79.45
223.20
462.44
  1989
511.32
146.43
346.37
1577.99
722.32
  1990
551.36
162.19
368.48
1635.85
790.96
  1991
606.11
185.24
398.62
1791.57
859.44
  1992
691.74
226.16
441.45
2017.83
969.55
  1993
817.58
285.98
501.00
2359.42
1112.97
  1994
941.95
349.74
560.33
2812.12
1269.23
  1995
1040.00
417.90
585.43
3501.52
1673.39
  1996
1100.08
488.02
575.03
4275.26
2100.74
  1997
1219.09
580.56
601.23
5206.79
2619.25
  1998
1319.30
654.83
627.89
5944.58
2974.06
  1999
1452.94
740.23
676.95
6727.49
3361.12
  2000
1608.91
853.73
716.32
7655.56
3746.51
  2001
1802.04
993.96
765.24
8455.04
4462.68
  2002
2053.17
1202.37
75.48
104.80
789.74
232.34
812.22
148.28
218.69
360.58
84.66
38.58
9362.03
4827.08
  
  Beijing
133.93
112.84
2.98
8.96
81.08
19.81
18.38
2.57
3.69
11.59
0.54
2.72
284.83
264.04
  Tianjin
48.33
32.43
1.24
2.72
13.92
14.54
14.26
1.46
2.44
7.02
3.34
1.64
130.53
126.58
  Hebei
135.74
71.61
2.82
1.24
48.44
19.12
60.50
19.95
8.88
24.02
7.65
3.62
577.02
298.44
  Shanxi
63.85
33.32
4.53
1.63
19.02
8.14
29.39
9.18
8.23
8.83
3.16
1.14
201.98
128.93
  Inner Mongolia
42.73
23.77
1.10
1.83
16.28
4.56
18.30
6.53
5.52
5.48
0.77
0.67
205.07
83.76
  
  Liaoning
88.68
52.42
3.24
2.84
42.16
4.18
35.13
11.27
3.66
19.38
0.82
1.13
346.75
232.26
  Jilin
47.57
29.68
1.60
1.28
22.99
3.81
17.72
3.60
6.95
6.57
0.60
0.17
213.77
170.21
  Heilongjiang
60.28
35.93
4.89
1.51
21.93
7.59
23.51
5.10
8.30
5.65
4.45
0.84
178.06
139.15
  
  Shanghai
62.30
45.09
3.18
6.03
31.76
4.12
17.21
2.30
6.30
6.06
2.55
189.63
148.57
  Jiangsu
104.50
65.17
3.72
7.83
41.10
12.53
37.39
2.63
18.47
13.38
2.92
1.93
729.71
234.69
  Zhejiang
107.83
58.78
2.78
5.67
39.52
10.81
46.97
1.41
13.80
25.40
6.36
2.07
456.08
199.36
  Anhui
54.66
26.73
2.68
2.70
15.91
5.44
25.86
2.20
12.72
9.36
1.58
2.07
206.39
170.87
  Fujian
43.63
22.69
1.36
3.14
15.08
3.11
19.82
0.98
5.02
9.98
3.84
1.12
315.51
104.59
  Jiangxi
30.31
13.83
1.27
0.77
10.53
1.25
15.71
7.09
2.20
6.18
0.24
0.77
208.93
102.65
  Shandong
150.53
82.14
3.54
7.43
48.58
22.60
64.79
5.18
17.00
34.61
7.99
3.60
814.70
291.17
  
  Henan
105.82
58.97
4.06
6.76
31.72
16.43
44.50
14.32
7.63
17.50
5.06
2.35
521.74
242.38
  Hubei
62.33
33.87
3.12
3.48
25.58
1.68
26.94
1.28
12.25
9.78
3.64
1.52
348.17
184.93
  Hunan
57.67
31.09
2.86
1.37
23.70
3.17
26.57
4.37
10.33
10.24
1.63
279.53
153.06
  Guangdong
230.89
130.29
7.92
13.57
104.32
4.48
97.39
16.30
11.32
67.05
2.72
3.21
1259.30
491.10
  Guangxi
40.14
23.21
1.99
1.52
10.90
8.81
15.99
2.98
4.93
4.68
3.40
0.94
355.40
112.11
  Hainan
10.94
6.25
0.57
0.15
5.44
0.09
4.51
1.74
0.18
2.52
0.07
0.18
70.45
40.13
  
  Chongqing
29.07
14.88
1.51
0.59
11.37
1.41
13.45
3.69
2.34
7.16
0.27
0.74
99.91
75.09
  Sichuan
98.97
60.93
4.07
3.46
25.92
27.48
36.99
1.14
15.67
13.38
6.80
1.05
472.25
270.18
  Guizhou
29.29
15.66
1.00
2.48
5.93
6.25
13.49
0.17
4.34
5.66
3.32
0.14
97.62
70.38
  Yunnan
69.94
38.18
1.49
2.72
23.00
10.98
31.42
5.42
9.07
9.24
7.69
0.34
257.24
147.16
  Tibet
5.87
3.12
0.14
0.41
2.52
0.06
2.72
2.09
0.33
0.12
0.18
0.03
8.20
7.03
  
  Shaanxi
48.34
32.38
2.07
9.83
15.01
5.47
14.62
1.80
7.31
4.38
1.13
1.34
215.98
148.73
  Gansu
25.68
13.49
1.23
1.41
8.10
2.76
11.66
1.26
5.11
4.32
0.98
0.53
105.00
56.05
  Qinghai
8.63
4.99
0.35
0.87
3.44
0.33
3.50
0.35
1.99
0.91
0.24
0.14
41.17
19.82
  Ningxia
9.59
4.89
0.39
0.35
3.37
0.77
4.31
0.48
1.74
1.69
0.39
0.40
42.21
20.88
  Xinjiang
45.15
23.73
1.78
0.27
21.13
0.56
19.22
9.46
0.96
8.46
0.34
2.20
128.86
92.80
  
                            
  a) Cars are included in passenger vehicles.(The same as in the following table.)
  b) Since 2002, the statistical standard of detail item of passenger vehicles and trucks, other vehicles have been adjusted, the data are not comparable with the previous years.(The same as in the following table.)
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