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List of Chinese prefecture-level cities by GDP
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This is a list of direct-controlled municipalities and provincial cities (in Mainland China) by gross domestic product (GDP).
Contents
[hide]
1 Methodology
2 2017 List
3 Historical Data
4 See also
5 Notes
6 References
Methodology[edit]
Shown here are GDP figures publicized in provincial-level Statistical Yearbooks or official statistical communiques.
All GDP figures are based on the national currency Chinese yuan (code:CN¥)，for an easy comparison they are converted into US dollars according to official average annual exchange rates, purchasing power parity (PPP) according to comparison of IMF WEO figures.
Shanghai is the biggest city by GDP in China
Beijing is the second biggest Chinese city in terms of GDP
Hong Kong SAR has the third highest GDP of all cities in China
Guangzhou, in Guangdong province, is the fourth largest city in China in economic terms
Shenzhen, also in Guangdong province, is the fifth biggest Chinese city in GDP terms
Suzhou, in Jiangsu province is the Chinese city with the sixth highest GDP
Tianjin is the seventh richest city in China
Chongqing is the eighth city with the highest GDP in China
Wuhan in Hubei province is the ninth biggest city in China in terms of GDP
Chengdu in Sichuan province is the tenth biggest city in Mainland China in GDP
Hangzhou in Zhejiang province is the eleventh biggest city in Mainland China in GDP
Wuxi, is the twelfth biggest city by GDP in Mainland China
2017 List[edit]
List of top cities by GDP over US$30 billions[1]
( gdp 2017, in bil. )
rank
city
Provinces
CN¥
US$
Intl$.
(PPP)
Shanghai Shanghai 3,013.39 446.31 859.42
Beijing Beijing 2,800.04 414.71 798.57
1 Shenzhen Guangdong[2] 2,243.84 332.33 639.94
2 Guangzhou Guangdong[2] 2,150.32 318.48 613.27
Chongqing Chongqing 1,950.03 288.82 556.15
Tianjin Tianjin 1,859.54 275.41 530.34
3 Suzhou Jiangsu[3] 1,731.95 256.52 493.95
4 Chengdu Sichuan[4] 1,388.94 205.71 396.13
5 Wuhan Hubei[5] 1,341.03 198.62 382.46
6 Hangzhou Zhejiang[6] 1,255.62 185.97 358.10
7 Nanjing Jiangsu[3] 1,171.51 173.51 334.12
8 Qingdao Shandong[7] 1,103.73 163.47 314.78
9 Changsha Hunan[8] 1,053.55 156.04 300.47
10 Wuxi Jiangsu[3] 1,051.18 155.69 299.80
11 Ningbo Zhejiang[6] 984.69 145.84 280.84
12 Foshan Guangdong[2] 954.96 141.44 272.36
13 Zhengzhou Henan[9] 913.02 135.23 260.39
14 Nantong Jiangsu[3] 773.46 114.56 220.59
15 Dongguan Guangdong[2] 758.21 112.30 216.24
16 Quanzhou Fujian[10] 754.80 111.79 215.27
17 Dalian Liaoning[11] 736.30 109.05 209.99
18 Yantai Shandong[7] 733.90 108.70 209.31
19 Hefei Anhui[12] 721.34 106.84 205.73
20 Jinan Shandong[7] 720.20 106.67 205.40
21 Tangshan Hebei[13] 710.61 105.25 202.67
22 Fuzhou Fujian[10] 710.40 105.22 202.61
23 Changzhou Jiangsu[3] 662.23 98.08 188.87
24 Xuzhou Jiangsu[3] 660.60 97.84 188.40
25 Changchun Jilin[14] 653.00 96.71 186.24
26 Harbin Heilongjiang[15] 635.50 94.12 181.25
27 Xi'an Shaanxi[16] 625.72 92.67 178.46
28 Shijiazhuang Hebei[13] 600.35 88.92 171.22
29 Shenyang Liaoning[11] 586.50 86.87 167.27
30 Weifang Shandong[7] 585.86 86.77 167.09
31 Wenzhou Zhejiang[6] 545.32 80.77 155.52
32 Shaoxing Zhejiang[6] 510.80 75.65 145.68
33 Yancheng Jiangsu[3] 508.27 75.28 144.96
34 Yangzhou Jiangsu[3] 506.49 75.02 144.45
35 Nanchang Jiangxi[17] 500.32 74.10 142.69
36 Kunming Yunnan[18] 485.76 71.95 138.54
37 Zibo Shandong[7] 478.13 70.82 136.36
38 Taizhou, Jiangsu Jiangsu[3] 474.45 70.27 135.31
39 Jining Shandong[7] 465.06 68.88 132.63
40 Ordos Inner Mongolia[19] 441.79 65.43 126.00
41 Taizhou, Zhejiang Zhejiang[6] 438.82 64.99 125.15
42 Jiaxing Zhejiang[6] 435.52 64.50 124.21
43 Xiamen Fujian[10] 435.12 64.44 124.10
44 Linyi Shandong[7] 434.54 64.36 123.93
45 Luoyang Henan[9] 434.31 64.33 123.87
46 Nanning Guangxi[20] 411.88 61.00 117.47
47 Zhenjiang Jiangsu[3] 410.54 60.80 117.09
48 Xiangyang Hubei[5] 406.49 60.20 115.93
49 Jinhua Zhejiang[6] 387.02 57.32 110.38
50 Yichang Hubei[5] 385.72 57.13 110.01
51 Huizhou Guangdong[2] 383.06 56.73 109.25
52 Cangzhou Hebei[13] 381.69 56.53 108.86
53 Dongying Shandong[7] 380.18 56.31 108.43
54 Handan Hebei[13] 366.63 54.30 104.56
55 Tai'an Shandong[7] 358.53 53.10 102.25
56 Zhangzhou Fujian[10] 356.35 52.78 101.63
57 Guiyang Guizhou[21] 353.80 52.40 100.90
58 Weihai Shandong[7] 348.01 51.54 99.25
59 Zhongshan Guangdong[2] 345.03 51.10 98.40
60 Huai'an Jiangsu[3] 338.75 50.17 96.61
61 Taiyuan Shanxi[22] 338.22 50.09 96.46
62 Nanyang Henan[9] 337.77 50.03 96.33
63 Yueyang Hunan[8] 325.80 48.25 92.92
64 Changde Hunan[8] 323.81 47.96 92.35
65 Baoding Hebei[13] 322.73 47.80 92.04
66 Dezhou Shandong[7] 314.82 46.63 89.79
67 Hengyang Hunan[8] 313.25 46.39 89.34
68 Wuhu Anhui[12] 306.55 45.40 87.43
69 Liaocheng Shandong[7] 306.41 45.38 87.39
70 Maoming Guangdong[2] 292.42 43.31 83.40
71 Langfang Hebei[13] 288.06 42.66 82.15
72 Zhanjiang Guangdong[2] 282.40 41.83 80.54
73 Heze Shandong[7] 282.02 41.77 80.43
74 Yulin, Shaanxi Shaanxi[16] 277.31 41.07 79.09
75 Liuzhou Guangxi[20] 275.56 40.81 78.59
76 Baotou Inner Mongolia[19] 275.30 40.77 78.52
77 Zunyi Guizhou[21] 274.86 40.71 78.39
78 Urumqi Xinjiang[23] 274.38 40.64 78.25
79 Hohhot Inner Mongolia[19] 274.37 40.64 78.25
80 Jiangmen Guangdong[2] 269.03 39.84 76.73
81 Daqing Heilongjiang[24] 268.00 39.69 76.43
82 Xuchang Henan[9] 264.21 39.13 75.35
83 Lianyungang Jiangsu[3] 264.03 39.11 75.30
84 Binzhou Shandong[7] 261.29 38.70 74.52
85 Suqian Jiangsu[3] 261.09 38.67 74.46
86 Zhuzhou Hunan[8] 258.04 38.22 73.59
87 Zhuhai Guangdong[2] 256.47 37.99 73.15
88 Ganzhou Jiangxi[17] 252.40 37.38 71.98
89 Lanzhou Gansu[25] 252.35 37.38 71.97
90 Zhoukou Henan[9] 251.70 37.28 71.79
91 Huzhou Zhejiang[6] 247.61 36.67 70.62
92 Jiujiang Jiangxi[17] 241.36 35.75 68.84
93 Xianyang Shaanxi[16] 239.61 35.49 68.34
94 Xinxiang Henan[9] 238.48 35.32 68.01
95 Shantou Guangdong[2] 235.08 34.82 67.04
96 Jiaozuo Henan[9] 234.28 34.70 66.82
97 Chenzhou Hunan[8] 233.77 34.62 66.67
98 Zaozhuang Shandong[7] 231.59 34.30 66.05
99 Jilin City Jilin[14] 230.28 34.11 65.68
100 Anyang Henan[9] 226.81 33.59 64.69
101 Xingtai Hebei[13] 223.64 33.12 63.78
102 Xinyang Henan[9] 222.66 32.98 63.50
103 Shangqiu Henan[9] 221.79 32.85 63.25
104 Zhaoqing Guangdong[2] 220.06 32.59 62.76
105 Zhumadian Henan[9] 219.55 32.52 62.62
106 Longyan Fujian[10] 216.75 32.10 61.82
107 Jieyang Guangdong[2] 215.14 31.86 61.36
108 Sanming Fujian[10] 213.61 31.64 60.92
109 Xiangtan Hunan[8] 205.58 30.45 58.63
110 Shangrao Jiangxi[17] 205.54 30.44 58.62
111 Putian Fujian[10] 204.52 30.29 58.33
112 Guilin Guangxi[20] 204.52 30.29 58.33
Historical Data[edit]
show
2013 List
List of top cities by GDP over US$20 billions[26]
( figures in 2013, in mil. )
rank
city
CN¥
US$
Intl$.
(PPP)
Provinces
Shanghai 2,181,815 352,292 600,571 Shanghai[26]
Beijing 1,980,081 319,719 545,041 Beijing[26]
1 Guangzhou 1,542,014 248,985 424,458 Guangdong[27]
2 Shenzhen 1,450,023 234,131 399,137 Guangdong[27]
Tianjin 1,444,201 233,191 397,534 Tianjin[26]
3 Suzhou 1,301,570 210,161 358,273 Jiangsu[28]
Chongqing 1,278,326 206,408 351,875 Chongqing[26]
4 Chengdu 910,889 147,079 250,733 Sichuan[29]
5 Wuhan 905,127 146,149 249,147 Hubei[30]
6 Hangzhou 834,352 134,721 229,666 Zhejiang[31]
7 Wuxi 807,018 130,307 222,142 Jiangsu[28]
8 Nanjing 801,178 129,364 220,534 Jiangsu[28]
9 Qingdao 800,660 129,281 220,391 Shandong[32]
10 Dalian 765,079 123,535 210,597 Liaoning[33]
11 Shenyang 715,857 115,588 197,048 Liaoning[33]
12 Changsha 715,313 115,500 196,899 Hunan[34]
13 Ningbo 712,887 115,108 196,231 Zhejiang[31]
14 Foshan 701,017 113,191 192,963 Guangdong[27]
15 Zhengzhou 620,190 100,140 170,715 Henan[35]
16 Tangshan 612,121 98,838 168,494 Hebei[36]
17 Yantai 561,387 90,646 154,529 Shandong[32]
18 Dongguan 549,002 88,646 151,119 Guangdong[27]
19 Jinan 523,019 84,451 143,967 Shandong[32]
20 Quanzhou 521,800 84,254 143,632 Fujian[37]
21 Nantong 503,889 81,362 138,702 Jiangsu[28]
22 Harbin 501,081 80,908 137,929 Heilongjiang[38]
23 Changchun 500,318 80,785 137,719 Jilin[39]
24 Xi'an 488,413 78,863 134,442 Shaanxi[40]
25 Shijiazhuang 486,366 78,532 133,878 Hebei[36]
26 Fuzhou 467,849 75,542 128,781 Fujian[37]
27 Hefei 467,291 75,452 128,628 Anhui[41]
28 Xuzhou 443,582 71,624 122,101 Jiangsu[28]
29 Weifang 442,070 71,380 121,685 Shandong[32]
30 Changzhou 436,093 70,415 120,040 Jiangsu[28]
31 Daqing 418,150 67,518 115,101 Heilongjiang[38]
32 Wenzhou 400,386 64,649 110,211 Zhejiang[31]
33 Shaoxing 396,729 64,059 109,204 Zhejiang[31]
34 Ordos 395,590 63,875 108,891 Inner Mongolia[42]
35 Zibo 380,124 61,378 104,634 Shandong[32]
36 Jining 350,154 56,538 96,384 Shandong[32]
37 Yancheng 347,550 56,118 95,667 Jiangsu[28]
38 Baotou 342,475 55,299 94,270 Inner Mongolia[42]
39 Kunming 341,531 55,146 94,011 Yunnan[43]
40 Linyi 333,681 53,879 91,850 Shandong[32]
41 Nanchang 333,603 53,866 91,828 Jiangxi[44]
42 Yangzhou 325,201 52,509 89,516 Jiangsu[28]
43 Dongying 325,020 52,480 89,466 Shandong[32]
44 Taizhou 315,334 50,916 86,800 Zhejiang[31]
45 Jiaxing 314,766 50,824 86,643 Zhejiang[31]
46 Luoyang 313,614 50,638 86,326 Henan[35]
47 Handan 306,150 49,433 84,272 Hebei[36]
48 Xiamen 301,816 48,733 83,079 Fujian[37]
49 Cangzhou 301,299 48,650 82,936 Hebei[36]
50 Taizhou, Jiangsu 300,691 48,552 82,769 Jiangsu[28]
51 Jinhua 295,878 47,775 81,444 Zhejiang[31]
52 Zhenjiang 292,728 47,266 80,577 Jiangsu[28]
53 Baoding 290,431 46,895 79,945 Hebei[36]
54 Yulin 284,675 45,966 78,360 Shaanxi[40]
55 Yichang 281,807 45,503 77,571 Hubei[30]
56 Xiangyang 281,402 45,437 77,459 Hubei[30]
57 Tai'an 279,070 45,061 76,817 Shandong[32]
58 Hohhot 270,539 43,683 74,469 Inner Mongolia[42]
59 Huizhou 267,835 43,247 73,725 Guangdong[27]
60 Nanning 266,197 42,982 73,274 Guangxi[45]
61 Zhongshan 263,893 42,610 72,640 Guangdong[27]
62 Anshan 262,325 42,357 72,208 Liaoning[33]
63 Jilin City 261,741 42,263 72,047 Jilin[39]
64 Weihai 254,969 41,169 70,183 Shandong[32]
65 Nanyang 250,000 40,367 68,816 Henan[35]
66 Dezhou 246,059 39,731 67,731 Shandong[32]
67 Yueyang 243,551 39,326 67,040 Hunan[34]
68 Taiyuan 241,287 38,960 66,417 Shanxi[46]
69 Ürümqi 240,000 38,752 66,063 Xinjiang[47]
70 Liaocheng 236,587 38,201 65,123 Shandong[32]
71 Changde 226,494 36,571 62,345 Hunan[34]
72 Zhangzhou 223,602 36,104 61,549 Fujian[37]
73 Hengyang 216,944 35,029 59,716 Hunan[34]
74 Maoming 216,017 34,880 59,461 Guangdong[27]
75 Huaian 215,586 34,810 59,343 Jiangsu[28]
76 Binzhou 215,573 34,808 59,339 Shandong[32]
77 Wuhu 209,953 33,901 57,792 Anhui[41]
78 Guiyang 208,542 33,673 57,404 Guizhou[48]
79 Zhanjiang 206,001 33,262 56,704 Guangdong[27]
80 Heze 205,001 33,101 56,429 Shandong[32]
81 Liuzhou 201,005 32,456 55,329 Guangxi[45]
82 Jiangmen 200,018 32,296 55,057 Guangdong[27]
83 Zhuzhou 194,943 31,477 53,660 Hunan[34]
84 Langfang 194,313 31,375 53,487 Hebei[36]
85 Xuchang 190,330 30,732 52,391 Henan[35]
86 Xianyang 186,039 30,039 51,210 Shaanxi[40]
87 Zaozhuang 183,063 29,559 50,390 Shandong[32]
88 Huzhou 180,315 29,115 49,634 Zhejiang[31]
89 Lianyungang 178,542 28,829 49,146 Jiangsu[28]
90 Tongliao 178,180 28,770 49,046 Inner Mongolia[42]
91 Lanzhou 177,628 28,681 48,894 Gansu[49]
92 Xinxiang 176,600 28,515 48,611 Henan[35]
93 Zhoukou 175,340 28,312 48,264 Henan[35]
94 Jiaozuo 170,736 27,568 46,997 Henan[35]
95 Suqian 170,628 27,551 46,967 Jiangsu[28]
96 Chifeng 168,615 27,226 46,413 Inner Mongolia[42]
97 Chenzhou 168,552 27,216 46,396 Hunan[34]
98 Anyang 168,400 27,191 46,354 Henan[35]
99 Ganzhou 167,331 27,019 46,060 Jiangxi[44]
100 Zhuhai 166,238 26,842 45,759 Guangdong[27]
101 Zhaoqing 166,007 26,805 45,695 Guangdong[27]
102 Guilin 165,790 26,770 45,636 Guangxi[45]
103 Songyuan 165,048 26,650 45,432 Jilin[39]
104 Jieyang 160,535 25,921 44,189 Guangdong[27]
105 Xingtai 160,458 25,909 44,168 Hebei[36]
106 Jiujiang 160,173 25,863 44,090 Jiangxi[44]
107 Zunyi 158,467 25,587 43,620 Guizhou[48]
108 Qujing 158,394 25,575 43,600 Yunnan[43]
109 Xinyang 158,116 25,531 43,523 Henan[35]
110 Shantou 156,590 25,284 43,103 Guangdong[27]
111 Pingdingshan 155,690 25,139 42,856 Henan[35]
112 Baoji 154,591 24,961 42,553 Shaanxi[40]
113 Shangqiu 153,820 24,837 42,341 Henan[35]
114 Yingkou 151,311 24,432 41,650 Liaoning[33]
115 Rizhao 150,016 24,223 41,294 Shandong[32]
116 Zhumadian 149,813 24,190 41,238 Henan[35]
117 Longyan 147,990 23,896 40,736 Fujian[37]
118 Sanming 147,759 23,858 40,672 Fujian[37]
119 Mianyang 145,512 23,495 40,054 Sichuan[29]
120 Xiangtan 144,306 23,301 39,722 Hunan[34]
121 Hulunbuir 143,081 23,103 39,385 Inner Mongolia[42]
122 Anqing 141,824 22,900 39,039 Anhui[41]
123 Shangrao 140,131 22,627 38,573 Jiangxi[44]
124 Deyang 139,594 22,540 38,425 Sichuan[29]
125 Yichun 138,707 22,397 38,181 Jiangxi[44]
126 Yan'an 135,414 21,865 37,274 Shaanxi[40]
127 Panjin 135,106 21,815 37,190 Liaoning[33]
128 Weinan 134,901 21,782 37,133 Shaanxi[40]
129 Jinzhou 134,493 21,716 37,021 Liaoning[33]
130 Yibin 134,289 21,683 36,965 Sichuan[29]
131 Putian 134,286 21,683 36,964 Fujian[37]
132 Fushun 134,045 21,644 36,898 Liaoning[33]
133 Jingzhou 133,493 21,555 36,746 Hubei[30]
134 Changzhi 133,372 21,535 36,712 Shanxi[46]
135 Huanggang 133,255 21,516 36,680 Hubei[30]
136 Nanchong 132,855 21,452 36,570 Sichuan[29]
137 Kaifeng 132,739 21,433 36,538 Henan[35]
138 Zhangjiakou 131,702 21,266 36,253 Hebei[36]
139 Maanshan 129,302 20,878 35,592 Anhui[41]
140 Chengde 127,209 20,540 35,016 Hebei[36]
141 Dazhou 124,541 20,109 34,281 Sichuan[29]
142 Xiaogan 123,893 20,005 34,103 Hubei[30]
143 Ningde 123,872 20,001 34,097 Fujian[37]
show
2011 List
List of top cities by GDP over CN¥ 100 billions[1]
( figures in 2011, in mil. )
rank
city
CN¥
US$
Intl$.
(PPP)
Provinces
Shanghai 1,919,569 297,202 466,708 Shanghai
Beijing 1,625,193 251,625 395,136 Beijing
1 Guangzhou 1,242,344 192,349 302,053 Guangdong[50]
2 Shenzhen 1,150,553 178,137 279,736 Guangdong[50]
Tianjin 1,130,728 175,068 274,916 Tianjin
3 Suzhou 1,071,699 165,929 260,564 Jiangsu[51]
Chongqing 1,001,137 155,004 243,408 Chongqing
4 Hangzhou 701,906 108,674 170,655 Zhejiang[52]
5 Chengdu 695,058 107,614 168,991 Sichuan[53]
6 Wuxi 688,015 106,524 167,278 Jiangsu[51]
7 Wuhan 676,220 104,697 164,410 Hubei[54]
8 Qingdao 661,560 102,428 160,846 Shandong[55]
9 Foshan 621,023 96,151 150,990 Guangdong[50]
10 Dalian 615,063 95,229 149,541 Liaoning[56]
11 Nanjing 614,552 95,150 149,417 Jiangsu[51]
12 Ningbo 605,924 93,814 147,319 Zhejiang[52]
13 Shenyang 591,571 91,591 143,830 Liaoning[56]
14 Changsha 561,933 87,003 136,624 Hunan[57]
15 Tangshan 544,245 84,264 132,323 Hebei[58]
16 Zhengzhou 497,985 77,102 121,076 Henan[59]
17 Yantai 490,683 75,971 119,301 Shandong[55]
18 Dongguan 473,539 73,317 115,132 Guangdong[50]
19 Jinan 440,629 68,221 107,131 Shandong[55]
20 Quanzhou 427,089 66,125 103,839 Fujian[60]
21 Harbin 424,219 65,681 103,141 Heilongjiang[61]
22 Shijiazhuang 408,268 63,211 99,263 Hebei[58]
23 Nantong 408,022 63,173 99,203 Jiangsu[51]
24 Changchun 400,308 61,979 97,327 Jilin[62]
25 Xi'an 386,258 59,803 93,912 Shaanxi[63]
26 Daqing 374,154 57,929 90,969 Heilongjiang[61]
27 Fuzhou 373,638 57,849 90,843 Fujian[60]
28 Hefei 363,662 56,305 88,418 Anhui[64]
29 Changzhou 358,099 55,444 87,065 Jiangsu[51]
30 Xuzhou 355,165 54,989 86,352 Jiangsu[51]
31 Weifang 354,184 54,837 86,113 Shandong[55]
32 Wenzhou 341,853 52,928 83,115 Zhejiang[52]
33 Shaoxing 333,200 51,589 81,011 Zhejiang[52]
34 Zibo 328,023 50,787 79,753 Shandong[55]
35 Ordos 321,854 49,832 78,253 Inner Mongolia[65]
36 Baotou 300,540 46,532 73,071 Inner Mongolia[65]
37 Jining 289,669 44,849 70,428 Shandong[55]
38 Taizhou 279,491 43,273 67,953 Zhejiang[52]
39 Handan 278,903 43,182 67,810 Hebei[58]
40 Yancheng 277,133 42,908 67,380 Jiangsu[51]
41 Linyi 277,045 42,894 67,358 Shandong[55]
42 Luoyang 270,276 41,846 65,713 Henan[59]
43 Nanchang 268,887 41,631 65,375 Jiangxi[66]
44 Jiaxing 267,709 41,449 65,088 Zhejiang[52]
45 Dongying 267,635 41,437 65,071 Shandong[55]
46 Yangzhou 263,030 40,724 63,951 Jiangsu[51]
47 Cangzhou 258,520 40,026 62,854 Hebei[58]
48 Xiamen 253,931 39,316 61,739 Fujian[60]
49 Kunming 250,985 38,859 61,022 Yunnan[67]
50 Jinhua 245,807 38,058 59,763 Zhejiang[52]
51 Baoding 244,990 37,931 59,565 Hebei[58]
52 Taizhou, Jiangsu 242,261 37,509 58,901 Jiangsu[51]
53 Anshan 239,876 37,139 58,321 Liaoning[56]
54 Zhenjiang 231,145 35,788 56,199 Jiangsu[51]
55 Tai'an 230,431 35,677 56,025 Shandong[55]
56 Yulin 229,225 35,490 55,732 Shaanxi[63]
57 Nanning 221,144 34,239 53,767 Guangxi[68]
58 Jilin City 220,805 34,187 53,685 Jilin[62]
59 Nanyang 220,231 34,098 53,545 Henan[59]
60 Zhongshan 219,320 33,957 53,324 Guangdong[50]
61 Hohhot 217,727 33,710 52,936 Inner Mongolia[65]
62 Yichang 214,070 33,144 52,047 Hubei[54]
63 Xiangyang 213,222 33,013 51,841 Hubei[54]
64 Weihai 211,095 32,683 51,324 Shandong[55]
65 Huizhou 209,308 32,407 50,889 Guangdong[50]
66 Taiyuan 208,012 32,206 50,574 Shanxi[69]
67 Dezhou 195,071 30,202 47,428 Shandong[55]
68 Liaocheng 191,942 29,718 46,667 Shandong[55]
69 Yueyang 189,949 29,409 46,183 Hunan[57]
70 Jiangmen 183,064 28,343 44,509 Guangdong[50]
71 Binzhou 181,758 28,141 44,191 Shandong[55]
72 Changde 181,119 28,042 44,036 Hunan[57]
73 Zhangzhou 176,820 27,377 42,991 Fujian[60]
74 Maoming 174,531 27,022 42,434 Guangdong[50]
75 Hengyang 173,430 26,852 42,166 Hunan[57]
76 Zhanjiang 170,023 26,324 41,338 Guangdong[50]
77 Urümqi 169,003 26,166 41,090 Xinjiang[70]
78 Huaian 169,000 26,166 41,089 Jiangsu[51]
79 Wuhu 165,824 25,674 40,317 Anhui[64]
80 Langfang 161,142 24,949 39,179 Hebei[58]
81 Xuchang 158,874 24,598 38,627 Henan[59]
82 Liuzhou 157,972 24,458 38,408 Guangxi[68]
83 Zhuzhou 156,427 24,219 38,032 Hunan[57]
84 Zaozhuang 156,168 24,179 37,969 Shandong[55]
85 Heze 155,652 24,099 37,844 Shandong[55]
86 Huzhou 152,006 23,535 36,957 Zhejiang[52]
87 Xinxiang 148,941 23,060 36,212 Henan[59]
88 Anyang 148,661 23,017 36,144 Henan[59]
89 Pingdingshan 148,461 22,986 36,096 Henan[59]
90 Tongliao 144,882 22,432 35,225 Inner Mongolia[65]
91 Jiaozuo 144,262 22,336 35,075 Henan[59]
92 Xingtai 142,892 22,124 34,742 Hebei[58]
93 Lianyungang 141,052 21,839 34,294 Jiangsu[51]
94 Zhoukou 140,749 21,792 34,221 Henan[59]
95 Zhuhai 140,493 21,752 34,158 Guangdong[50]
96 Guiyang 138,307 21,414 33,627 Guizhou[71]
97 Xianyang 136,132 21,077 33,098 Shaanxi[63]
98 Songyuan 136,097 21,072 33,089 Jilin[62]
99 Lanzhou 136,003 21,057 33,067 Gansu[72]
100 Chifeng 134,719 20,858 32,754 Inner Mongolia[65]
101 Chenzhou 134,638 20,846 32,735 Hunan[57]
102 Ganzhou 133,600 20,685 32,482 Jiangxi[66]
103 Guilin 132,757 20,554 32,277 Guangxi[68]
104 Zhaoqing 132,441 20,506 32,201 Guangdong[50]
105 Suqian 132,083 20,450 32,114 Jiangsu[51]
106 Shangqiu 130,837 20,257 31,811 Henan[59]
107 Shantou 127,574 19,752 31,017 Guangdong[50]
108 Xinyang 125,768 19,472 30,578 Henan[59]
109 Jiujiang 125,641 19,453 30,547 Jiangxi[66]
110 Zhumadian 124,477 19,272 30,264 Henan[59]
111 Longyan 124,215 19,232 30,201 Fujian[60]
112 Jieyang 122,586 18,980 29,805 Guangdong[50]
113 Yingkou 122,465 18,961 29,775 Liaoning[56]
114 Changzhi 121,860 18,867 29,628 Shanxi[69]
115 Anqing 121,574 18,823 29,558 Anhui[64]
116 Rizhao 121,407 18,797 29,518 Shandong[55]
117 Sanming 121,181 18,762 29,463 Fujian[60]
118 Qujing 120,993 18,733 29,417 Yunnan[67]
119 Mianyang 118,911 18,411 28,911 Sichuan[53]
120 Baoji 117,575 18,204 28,586 Shaanxi[63]
121 Hulunbuir 114,531 17,733 27,846 Inner Mongolia[65]
122 Maanshan 114,430 17,717 27,822 Anhui[64]
123 Deyang 113,745 17,611 27,655 Sichuan[53]
124 Linfen 113,606 17,589 27,621 Shanxi[69]
125 Lüliang 113,071 17,507 27,491 Shanxi[69]
126 Xiangtan 112,414 17,405 27,331 Hunan[57]
127 Zunyi 112,146 17,363 27,266 Guizhou[71]
128 Panjin 111,992 17,339 27,229 Liaoning[56]
129 Zhangjiakou 111,861 17,319 27,197 Hebei[58]
130 Jinzhou 111,693 17,293 27,156 Liaoning[56]
131 Fushun 111,337 17,238 27,070 Liaoning[56]
132 Yan'an 111,335 17,238 27,069 Shaanxi[63]
133 Shangrao 111,058 17,195 27,002 Jiangxi[66]
134 Chengde 110,420 17,096 26,847 Hebei[58]
135 Yibin 109,118 16,894 26,530 Sichuan[53]
136 Yichun 107,798 16,690 26,209 Jiangxi[66]
137 Kaifeng 107,242 16,604 26,074 Henan[59]
138 Qinhuangdao 107,008 16,568 26,017 Hebei[58]
139 Qiqihar 106,567 16,500 25,910 Heilongjiang[61]
140 Putian 105,062 16,266 25,544 Fujian[60]
141 Huanggang 104,511 16,181 25,410 Hubei[54]
142 Benxi 104,459 16,173 25,397 Liaoning[56]
143 Jingzhou 104,312 16,150 25,362 Hubei[54]
144 Sanmenxia 103,045 15,954 25,053 Henan[59]
145 Nanchong 102,948 15,939 25,030 Sichuan[53]
146 Weinan 102,897 15,931 25,018 Shaanxi[63]
147 Yulin, Guangxi 101,994 15,791 24,798 Guangxi[68]
148 Yuncheng 101,682 15,743 24,722 Shanxi[69]
149 Dazhou 101,183 15,666 24,601 Sichuan[53]
150 Qingyuan 100,303 15,530 24,387 Guangdong[50]
Liangshan Prefecture 100,013 15,485 24,316 Sichuan[53]
show
2010 List
List of top cities by GDP over CN¥ 100 billions
( figures in 2010, in mil. )
rank
city
Provinces
CN¥
US$
Intl$.
(PPP)
1 Shanghai Shanghai[73] 1,716,598 253,578 435,022
Hong Kong Hong Kong[74] 1,519,423 224,458 324,966
2 Beijing Beijing[73] 1,411,358 208,488 357,668
3 Guangzhou Guangdong[75] 1,074,828 158,775 272,384
4 Shenzhen Guangdong[75] 958,151 141,539 242,816
5 Suzhou Jiangsu[76] 922,891 136,331 233,880
6 Tianjin Tianjin[73] 922,446 136,265 233,767
7 Chongqing Chongqing[73] 792,558 117,078 200,851
8 Hangzhou Zhejiang[77] 594,917 87,882 150,765
9 Wuxi Jiangsu[76] 579,330 85,579 146,814
10 Qingdao Shandong[78] 566,619 83,702 143,593
11 Foshan Guangdong[75] 565,152 83,485 143,221
12 Wuhan Hubei[79] 556,593 82,221 141,052
13 Chengdu Sichuan[80] 555,133 82,005 140,682
14 Ningbo Zhejiang[77] 516,300 76,269 130,841
15 Dalian Liaoning[81] 515,816 76,197 130,719
16 Nanjing Jiangsu[76] 513,065 75,791 130,022
17 Shenyang Liaoning[81] 501,754 74,120 127,155
18 Changsha Hunan[82] 454,706 67,170 115,232
19 Tangshan Hebei[83] 446,916 66,019 113,258
20 Yantai Shandong[78] 435,846 64,384 110,453
21 Dongguan Guangdong[75] 424,645 62,729 107,614
22 Zhengzhou Henan[84] 404,089 59,693 102,405
23 Ji'nan Shandong[78] 391,053 57,767 99,101
24 Harbin Heilongjiang[85] 366,485 54,138 92,875
25 Quanzhou Fujian[86] 356,497 52,662 90,344
26 Nantong Jiangsu[76] 346,567 51,195 87,827
27 Shijiazhuang Hebei[83] 340,102 50,240 86,189
28 Changchun Jilin[87] 332,903 49,177 84,365
29 Xi'an Shaanxi[88] 324,169 47,887 82,151
30 Fuzhou Fujian[86] 312,341 46,139 79,154
31 Weifang Shandong[78] 309,092 45,660 78,330
32 Changzhou Jiangsu[76] 304,489 44,980 77,164
33 Xuzhou Jiangsu[76] 294,214 43,462 74,560
34 Wenzhou Zhejiang[77] 292,504 43,209 74,127
35 Daqing Heilongjiang[85] 290,006 42,840 73,494
36 Zibo Shandong[78] 286,675 42,348 72,650
37 Shaoxing Zhejiang[77] 279,520 41,291 70,836
38 Hefei Anhui[89] 270,161 39,909 68,465
39 Ordos Inner Mongolia[90] 264,323 39,046 66,985
40 Jining Shandong[78] 254,281 37,563 64,440
41 Baotou Inner Mongolia[90] 246,080 36,351 62,362
42 Taizhou Zhejiang[77] 242,645 35,844 61,491
43 Linyi Shandong[78] 239,999 35,453 60,821
44 Handan Hebei[83] 236,156 34,885 59,847
45 Dongying Shandong[78] 235,994 34,861 59,806
46 Yancheng Jiangsu[76] 233,276 34,460 59,117
47 Luoyang Henan[84] 232,025 34,275 58,800
48 Jiaxing Zhejiang[77] 230,020 33,979 58,292
49 Yangzhou Jiangsu[76] 222,949 32,934 56,500
50 Nanchang Jiangxi[91] 220,711 32,604 55,933
51 Cangzhou Hebei[83] 220,312 32,545 55,832
52 Anshan Liaoning[81] 212,501 31,391 53,852
53 Kunming Yunnan[92] 212,030 31,321 53,733
54 Jinhua Zhejiang[77] 211,004 31,170 53,473
55 Xiamen Fujian[86] 206,007 30,432 52,207
56 Tai'an Shandong[78] 205,168 30,308 51,994
57 Baoding Hebei[83] 205,030 30,287 51,959
58 Taizhou Jiangsu[76] 204,872 30,264 51,919
59 Zhenjiang Jiangsu[76] 198,764 29,362 50,371
60 Nanyang Henan[84] 195,336 28,855 49,502
61 Weihai Shandong[78] 194,470 28,727 49,283
62 Hohhot Inner Mongolia[90] 186,571 27,561 47,281
63 Zhongshan Guangdong[75] 185,065 27,338 46,899
64 Jilin Jilin[87] 180,064 26,599 45,632
65 Nanning Guangxi[93] 180,026 26,594 45,622
66 Taiyuan Shanxi[94] 177,805 26,266 45,060
67 Yulin Shaanxi[88] 175,667 25,950 44,518
68 Huizhou Guangdong[75] 172,995 25,555 43,841
69 Dezhou Shandong[78] 165,782 24,490 42,013
70 Liaocheng Shandong[78] 162,238 23,966 41,115
71 Jiangmen Guangdong[75] 157,042 23,198 39,798
72 Yibin Sichuan[80] 155,152 22,919 39,319
73 Yichang Hubei[79] 154,732 22,857 39,212
74 Yueyang Hunan[82] 153,936 22,740 39,011
75 Xiangyang Hubei[79] 153,830 22,724 38,984
76 Maoming Guangdong[75] 149,209 22,041 37,813
77 Changde Hunan[82] 149,157 22,034 37,800
78 Zhangzhou Fujian[86] 143,071 21,135 36,257
79 Hengyang Hunan[82] 142,034 20,981 35,994
80 Zhanjiang Guangdong[75] 140,506 20,756 35,607
81 Huai'an Jiangsu[76] 138,807 20,505 35,177
82 Zaozhuang Shandong[78] 136,204 20,120 34,517
83 Langfang Hebei[83] 135,110 19,959 34,240
84 Ürümqi Xinjiang[95] 133,852 19,773 33,921
85 Xuchang Henan[84] 131,649 19,447 33,363
86 Anyang Henan[84] 131,559 19,434 33,340
87 Liuzhou Guangxi[93] 131,531 19,430 33,333
88 Pingdingshan Henan[84] 131,084 19,364 33,219
89 Huzhou Zhejiang[77] 130,173 19,229 32,989
90 Zhuzhou Hunan[82] 127,548 18,842 32,323
91 Jiaozuo Henan[84] 124,593 18,405 31,575
92 Zhoukou Henan[84] 122,830 18,145 31,128
93 Heze Shandong[78] 122,709 18,127 31,097
94 Xingtai Hebei[83] 121,209 17,905 30,717
95 Shantou Guangdong[75] 120,897 17,859 30,638
96 Zhuhai Guangdong[75] 120,860 17,854 30,628
97 Lianyungang Jiangsu[76] 119,331 17,628 30,241
98 Xinxiang Henan[84] 118,994 17,578 30,156
99 Tongliao Inner Mongolia[90] 117,662 17,381 29,818
100 Shangqiu Henan[84] 114,379 16,896 28,986
101 Guiyang Guizhou[96] 112,182 16,572 28,429
102 Ganzhou Jiangxi[91] 111,974 16,541 28,377
103 Wuhu Anhui[89] 110,863 16,377 28,095
104 Guilin Guangxi[93] 110,356 16,302 27,967
105 Songyuan Jilin[87] 110,285 16,291 27,948
106 Lanzhou Gansu[97] 110,039 16,255 27,886
107 Xianyang Shaanxi[88] 109,868 16,230 27,843
108 Xinyang Henan[84] 109,183 16,129 27,669
109 Qingyuan Guangdong[75] 108,818 16,075 27,577
110 Chifeng Inner Mongolia[90] 108,623 16,046 27,527
111 Zhaoqing Guangdong[75] 108,587 16,041 27,518
112 Chenzhou Hunan[82] 108,176 15,980 27,414
113 Suqian Jiangsu[76] 106,409 15,719 26,966
114 Zhumadian Henan[84] 105,371 15,566 26,703
115 Jiujiang Jiangxi[91] 103,206 15,246 26,155
116 Rizhao Shandong[78] 102,508 15,143 25,978
117 Jieyang Guangdong[75] 100,951 14,913 25,583
118 Qujing Yunnan[92] 100,560 14,855 25,484
119 Yingkou Liaoning[81] 100,245 14,808 25,404
See also[edit]
Economy of China
Historical GDP of China
List of Chinese administrative divisions by GDP
List of Chinese administrative divisions by GDP per capita
Top prefecture-level cities by GDP per capita
Prefecture-level city
List of cities in China by population
List of cities in China
List of twin towns and sister cities in China
List of capitals in China
Sub-provincial divisions in Mainland China
List of country subdivisions by GDP over 100 billion US dollars
List of urban agglomerations in China
List of Renminbi exchange rates
Sub-provincial divisions in China
Provincial city
Administrative divisions of China
Global city
Notes[edit]
^ The annual average exchange rate of CNY to HKD: CNY 0.8713 per HKD in 2010.
^ The annual average exchange rate is CNY (Renminbi) 6.7695 per USD; 7.7692 Hong Kong dollar (HKD) per United States dollar in 2010. also see List of Historical Chinese yuan exchange rates.
^ All the GDP figures are recent statistical revisions from statistical yearbooks of provinces pubulished in later 2011.
^ According to IMF WEO data, the PPP is CNY 3.9460 per international currency in 2010. Hong Kong GDP PPP is from IMF WEO data (September 2011).
References[edit]
Jump up ^ Nominal GDP is based on the official annual average exchange rate at CN¥ 6.7518 per US dollar; PPP GDP is based on IMF WEO Data April 2018, the average exchange rate is CN¥ 3.5063 per International dollar.
^ Jump up to: a b c d e f g h i j k l m gdstats.gov (2018-01-26)
^ Jump up to: a b c d e f g h i j k l m phb123.com (018-01-27)
Jump up ^ sc.gov (2018-01-31)
^ Jump up to: a b c sohu.com (2018-02-04)
^ Jump up to: a b c d e f g h phb123.com (2018-02-02)
^ Jump up to: a b c d e f g h i j k l m n o baidu.com (2018-02-08)
^ Jump up to: a b c d e f g hntj.gov (2018-01-31)
^ Jump up to: a b c d e f g h i j k qihoo.com (2018-04-23 ) or sohu.com
^ Jump up to: a b c d e f g sohu.com (2018-03-04)
^ Jump up to: a b sina.com (2018-04-09)
^ Jump up to: a b sohu.com (2018-03-16)
^ Jump up to: a b c d e f g hebei.gov (2018-03-02)
^ Jump up to: a b sina.com (2018-02-18)
Jump up ^ mnw.cn (2018-02-11 )
^ Jump up to: a b c mnw.cn (2018-01-24)
^ Jump up to: a b c d askci.com (2018-01-23)
Jump up ^ sc.gov (2018-02-26)
^ Jump up to: a b c baidu.com (2018-04-13)
^ Jump up to: a b c sohu.com (2018-02-02)
^ Jump up to: a b mnw.cn (2018-02-09)
Jump up ^ taiyuan.gov (2018-03-23)
Jump up ^ wenming.cn (2018-04-13)
Jump up ^ baidu.com (2018-03-10)
Jump up ^ lanzhou.gov (2018-02-06)
^ Jump up to: a b c d e the 2013 GDP figures of Shanghai, Beijing, Tianjin and Chongqing are revisions based on China Economic Census 2013, see China NBS: National Data - Regional - annual by province; Nominal GDP is based on the official annual average exchange rate at CN¥ 6.1932 per US dollar; PPP GDP is based on IMF WEO Data October 2014, the average exchange rate is CN¥ 3.6329 per International dollar.
^ Jump up to: a b c d e f g h i j k l m GDP 2013 figure of Guangdong divisions is from Guangdong statistical Yearbook 2014
^ Jump up to: a b c d e f g h i j k l m GDP 2013 figure of Jiangsu divisions is from Jiangsu statistical Yearbook 2014(Chinese)
^ Jump up to: a b c d e f GDP 2013 figure of Sichuan divisions is from Sichuan statistical Yearbook 2014(Chinese/English)
^ Jump up to: a b c d e f GDP 2013 figure of Hubei divisions is from Hubei statistical Yearbook 2014(Chinese/English)
^ Jump up to: a b c d e f g h GDP 2013 figure of Zhejiang divisions is from Zhejiang statistical Yearbook 2014(Chinese)
^ Jump up to: a b c d e f g h i j k l m n o p GDP 2013 figure of Shandong divisions is from Shandong statistical Yearbook 2014(Chinese)
^ Jump up to: a b c d e f g GDP 2013 figure of Liaoning divisions is from Liaoning statistical Yearbook 2014(Chinese)
^ Jump up to: a b c d e f g GDP 2013 figure of Hunan divisions is from Hunan statistical Yearbook 2014(Chinese/English)
^ Jump up to: a b c d e f g h i j k l m GDP 2013 figure of Henan divisions is from Henan statistical Yearbook 2014(Chinese/English)
^ Jump up to: a b c d e f g h i see local Statistical Communiqué 2013 of Hebei cities: Shijiazhuang, Handan, Cangzhou, Baoding, Langfang, Xingtai, Zhangjiakou, Chengde, Chengde (Chinese/中文)
^ Jump up to: a b c d e f g h GDP 2013 figure of Fujian divisions is from Fujian statistical Yearbook 2014(Chinese)
^ Jump up to: a b see local Statistical Communiqué 2013 of Heilongjiang cities: Daqing, Harbin (Chinese/中文)
^ Jump up to: a b c see local Statistical Communiqué 2013 of Jilin cities: Jilin city, Changchun, Songyuan (Chinese/中文)
^ Jump up to: a b c d e f GDP 2013 figure of Shaanxi divisions is from Shaanxi statistical Yearbook 2014(Chinese/English)
^ Jump up to: a b c d GDP 2013 figure of Anhui divisions is from Anhui statistical Yearbook 2014(Chinese/English)
^ Jump up to: a b c d e f see local Statistical Communiqué 2013 of Inner Mongolian cities: Baotou, Hohhot, Tongliao, Chifeng, Hulunbuir, (Chinese/中文)
^ Jump up to: a b see local Statistical Communiqué 2013 of Yunnan cities: Kunming, Qujing (Chinese/中文)
^ Jump up to: a b c d e GDP 2013 figure of Jiangxi divisions is from Jiangxi statistical Yearbook 2014(Chinese/English)
^ Jump up to: a b c GDP 2013 figure of Guangxi divisions is from Guangxi statistical Yearbook 2014(Chinese)
^ Jump up to: a b see local Statistical Communiqué 2013 of Shanxi cities: Taiyuan Archived 2015-07-14 at the Wayback Machine., Changzhi (Chinese/中文)
Jump up ^ GDP 2013 figure of Xinjiang divisions is from Xinjiang statistical Yearbook 2014(Chinese)
^ Jump up to: a b see local Statistical Communiqué 2013 of Guizhou cities: Guiyang, Zunyi (Chinese/中文)
Jump up ^ see local Statistical Communiqué 2013 of Lanzhou city, Gansu: Lanzhou (Chinese/中文)
^ Jump up to: a b c d e f g h i j k l m n GDP 2011 figure of Guangdong divisions is from Guangdong Statistical Yearbook 2012( ISBN 978-7-89468-203-1/F.403 )
^ Jump up to: a b c d e f g h i j k l m GDP 2011 figure of Jiangsu divisions is from Jiangsu statistical Yearbook 2012( ISBN 978-7-5037-6591-9 )
^ Jump up to: a b c d e f g h GDP 2011 figure of Zhejiang divisions is from Zhejiang statistical Yearbook 2012(ISBN 9787503766008 )
^ Jump up to: a b c d e f g GDP 2011 figure of Sichuan divisions is from Sichuan Statistical Yearbook 2012 (ISBN 978-7-89468-249-9. /F·44 )
^ Jump up to: a b c d e GDP 2011 figure of Hubei divisions is from Hubei Statistical Yearbook 2012(ISBN 978-7-5037-6633-6 )
^ Jump up to: a b c d e f g h i j k l m n o p GDP 2011 figure of Shandong divisions is from Shandong statistical Yearbook 2012( ISBN 9787503765841 )
^ Jump up to: a b c d e f g h GDP 2011 figure of Liaoning divisions is from Liaoning Statistical Yearbook 2012( ISBN 978-7-89468-271-0/F.471 )
^ Jump up to: a b c d e f g GDP 2011 figure of Hunan divisions is from Hunan statistical Yearbook 2012( ISBN 978-7-89468-292-5/F·492 )
^ Jump up to: a b c d e f g h i j GDP 2011 figure of Hebei divisions is from Hebei Statistical Yearbook 2012( ISBN 9787503766930 )
^ Jump up to: a b c d e f g h i j k l m n GDP 2011 figure of Henan divisions is from Henan Statistical Yearbook 2012( ISBN 7503766700 )
^ Jump up to: a b c d e f g GDP 2011 figure of Fujian divisions is from Fujian Statistical Yearbook 2012( ISBN 978-7-5037-6614-5 )
^ Jump up to: a b c GDP 2011 figure of Helongjiang divisions is from Heilongjiang statistical Yearbook 2012( ISBN 9787503766329 )
^ Jump up to: a b c GDP 2011 figure of Jilin divisions is from Jilin statistical Yearbook 2012( ISBN 9787503766732 )
^ Jump up to: a b c d e f GDP 2011 figure of Shaanxi divisions is from Shaanxi Statistical Yearbook 2012(ISBN 9787503765933 )
^ Jump up to: a b c d GDP 2011 figure of Anhui divisions is from Anhui statistical Yearbook 2012( ISBN 9787503765810 )
^ Jump up to: a b c d e f GDP 2011 figure of Inner Mongolian divisions is from Inner Mongolian statistical Yearbook 2012(ISBN 978-7-89468-268-0/F.468)
^ Jump up to: a b c d e GDP 2011 figure of Jiangxi divisions is from Jiangxi statistical Yearbook 2012(ISBN 978-7-5037-6648-0 )
^ Jump up to: a b GDP 2011 figure of Yunnan divisions is from Yunnan statistical Yearbook 2012( ISBN 9787541665929 )
^ Jump up to: a b c d GDP 2011 figure of Guangxi divisions is from Guangxi Statistical Yearbook 2012( ISBN 978-7-89468-261-1 )
^ Jump up to: a b c d e GDP 2011 figure of Shanxi divisions is from Shanxi Statistical Yearbook 2012( ISBN 978-7-89468-255-0 )
Jump up ^ GDP 2011 figure of Xinjiang divisions is from Heilongjiang statistical Yearbook 2012( ISBN 7503766875 )
^ Jump up to: a b GDP 2011 figure of Guizhou divisions is from Guizhou statistical Yearbook 2012( ISBN 9787503766800 )
Jump up ^ GDP 2011 figure of Gansu divisions is from Gansu statistical Yearbook 2012( ISBN 978-7-89468-257-4/F.457 )
^ Jump up to: a b c d GDP figure of Shangshai, Beijing, Tianjin and Chongqing 4 municipalities is according to China Statistical Yearbook 2011(ISBN 978-7-89468-215-4/F.415)
Jump up ^ Original GDP figure of Hong Kong SAR is HK$ 1,743,858 mil. (revision, instead of the former 1,748,090 mil.) from Hong Kong Census and Statistics Department, It is converted into CN¥ 1,519,423 mil. ( CN¥ 0.8713 per HK$) or US$ 224,458 mil. (HK$ 7.7692 per US$).
^ Jump up to: a b c d e f g h i j k l m n GDP figure of Guangdong cities is from Guangdong Statistical Yearbook 2011(ISBN 978-7-89468-203-1/F.403)
^ Jump up to: a b c d e f g h i j k l m GDP figure of Jiangsu cities is from Jiangsu Statistical Yearbook 2011(ISBN 978-7-89468-190-4/F.390)
^ Jump up to: a b c d e f g h GDP figure of Zhejiang cities is from Zhejiang Statistical Yearbook 2011(ISBN 978-7-5037-6257-4)
^ Jump up to: a b c d e f g h i j k l m n o GDP figure of Shandong cities is from Shandong Statistical Yearbook 2011(ISBN 978-7-89468-199-7/F.399)
^ Jump up to: a b c GDP figure of Hubei cities is from Hubei Statistical Yearbook 2011(ISBN 978-7-89468-213-0/F.413)
^ Jump up to: a b GDP figure of Chengdu is from Sichuan Statistical Yearbook 2011(ISBN 978-7-5037-6298-7)
^ Jump up to: a b c d GDP figure of Liaoning cities is from Liaoning Statistical Yearbook 2011(ISBN 978-7-89468-219-2/F.419)
^ Jump up to: a b c d e f GDP figure of Hunan cities is from Hunan Statistical Yearbook 2011(ISBN 978-7-89468-208-6/F.408)
^ Jump up to: a b c d e f g GDP figure of Hebei cities is from Hebei Statistical Yearbook 2011(ISBN 978-7-89468-232-1/F.432)
^ Jump up to: a b c d e f g h i j k l GDP figure of Henan cities is from Henan Statistical Yearbook 2011(ISBN 978-7-89468-218-5/F.418)
^ Jump up to: a b GDP figure of Heilongjiang cities is from Heilongjiang Statistical Yearbook 2011(ISBN 978 7 5037-6326-7)
^ Jump up to: a b c d GDP figure of Fujian cities is from Fujian Statistical Yearbook 2011(ISBN 978-7-5037-6288-8)
^ Jump up to: a b c GDP figure of Jilin cities is from Jilin Statistical Yearbook 2011(ISBN 978-7-5037-6320-5)
^ Jump up to: a b c GDP figure of Shaanxi cities is from Shaanxi Statistical Yearbook 2011(ISBN 978-7-89468-194-2/F.394)
^ Jump up to: a b GDP figure of Anhui cities is from Anhui Statistical Yearbook 2011(ISBN 978-7-89468-206-2/F.406)
^ Jump up to: a b c d e GDP figure of Inner Mongolian cities is from Inner Mongolian Statistical Yearbook 2011 (ISBN 978-7-5037-6335-9. /F.413)
^ Jump up to: a b c GDP figure of Jiangxi cities is from Jiangxi Statistical Yearbook 2011(ISBN 978-7-89468-202-4/F.402)
^ Jump up to: a b GDP figure of Yunnan cities is from Yunnan Statistical Yearbook 2011(ISBN 978-7-5037-6302-1)
^ Jump up to: a b c GDP figure of Guangxi cities is from Guangxi Statistical Yearbook 2011(ISBN 978-7-89468-217-8/F.417)
Jump up ^ GDP figure of Taiyuan is from Shanxi Statistical Yearbook 2011(ISBN 978-7-89468-193-5)
Jump up ^ GDP figure of Ürümqi is from Xinjiang Statistical Yearbook 2011(ISBN 978-7-89468-210-9/F.410)
Jump up ^ GDP figure of Guiyang is from Guizhou Statistical Yearbook 2011
Jump up ^ GDP figure of Lanzhou is from Gansu Development Yearbook 2011(ISBN 978-7-89468-224-6/F·424)
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Active transport
From Wikipedia, the free encyclopedia
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This article is about transport in cellular biology. For human transport systems, see active transportation.
Active transport is the movement of molecules across a [natemembrane]] from a region of their lower concentration to a region of their higher concentration—in the direction against some gradient or other obstructing factor (often a concentration gradient).
Unlike passive transport, which uses the kinetic energy and natural entropy of molecules moving down a gradient, active transport uses cellular energy to move them against a gradient, polar repulsion, or other resistance. Active transport is usually associated with accumulating high concentrations of molecules that the cell needs, such as ions, glucose and amino acids. If the process uses chemical energy, such as from adenosine triphosphate (ATP), it is termed primary active transport. Secondary active transport involves the use of an electrochemical gradient. Examples of active transport include the uptake of glucose in the intestines in humans and the uptake of mineral ions into root hair cells of plants.[1]
Contents
[hide]
1 History
2 Details
3 Primary active transport
3.1 Model of active transport
4 Types of ATP-powered primary active transporters
5 Secondary active transport
5.1 Antiport
5.2 Symport
6 Examples
7 Endocytosis and exocytosis
8 See also
9 References
10 Notes
11 External links
History[edit]
In 1848, the German physiologist Emil Heinrich du Bois-Reymond suggested the possibility of active transport of substances across membranes.[2]
Rosenberg (1948) formulated the concept of active transport based on energetic considerations,[3] but later it would be redefined.
Details[edit]
Specialized transmembrane proteins recognize the substance and allow it to move across the membrane when it otherwise would not, either because the phospholipid bilayer of the membrane is impermeable to the substance moved or because the substance is moved against the direction of its concentration gradient.[4] There are two forms of active transport, primary active transport and secondary active transport. In primary active transport, the proteins involved are pumps that normally use the chemical energy in the form of ATP. Secondary active transport, however, makes use of potential energy, which are usually derived through exploitation of an electrochemical gradient. This involves pore-forming proteins that form channels across the cell membrane. The difference between passive transport and active transport is active transport requires energy and moves substances against their respective concentration gradient, whereas passive transport requires no energy and moves substances in the direction of their respective concentration gradient.
In an antiporter, one substrate is transported in one direction across the membrane while another is cotransported in the opposite direction. In a symporter, two substrates are transported in the same direction across the membrane. Antiport and symport processes are associated with secondary active transport, meaning that one of the two substances is transported in the direction of its concentration gradient, utilizing the energy derived from the transport of such substance (mostly Na+, K+ or H+ ions) down its concentration gradient.
If substrate molecules are moving from areas of lower concentration to areas of higher concentration[5] (i.e., in the opposite direction as, or against the concentration gradient), specific transmembrane carrier proteins are required. These proteins have receptors that bind to specific molecules (e.g., glucose) and transport them across the cell membrane. Because energy is required in this process, it is known as 'active' transport. Examples of active transport include the transportation of sodium out of the cell and potassium into the cell by the sodium-potassium pump. Active transport often takes place in the internal lining of the small intestine.
Plants need to absorb mineral salts from the soil or other sources, but these salts exist in very dilute solution. Active transport enables these cells to take up salts from this dilute solution against the direction of the concentration gradient.
Primary active transport[edit]
The action of the sodium-potassium pump is an example of primary active transport.
Primary active transport, also called direct active transport, directly uses metabolic energy to transport molecules across a membrane.[6]
Most of the enzymes that perform this type of transport are transmembrane ATPases. A primary ATPase universal to all animal life is the sodium-potassium pump, which helps to maintain the cell potential. The sodium-potassium pump maintains the membrane potential by moving three Na+ ions out of the cell for every two [7] K+ ions moved into the cell. Other sources of energy for Primary active transport are redox energy and photon energy (light). An example of primary active transport using Redox energy is the mitochondrial electron transport chain that uses the reduction energy of NADH to move protons across the inner mitochondrial membrane against their concentration gradient. An example of primary active transport using light energy are the proteins involved in photosynthesis that use the energy of photons to create a proton gradient across the thylakoid membrane and also to create reduction power in the form of NADPH.
Model of active transport[edit]
ATP hydrolysis is used to transport hydrogen ions against the electrochemical gradient (from low to high hydrogen ion concentration). Phosphorylation of the carrier protein and the binding of a hydrogen ion induce a conformational (shape) change that drives the hydrogen ions to transport against the electrochemical gradient. Hydrolysis of the bound phosphate group and release of hydrogen ion then restores the carrier to its original conformation.[8]
Types of ATP-powered primary active transporters[edit]
P-type ATPase: sodium potassium pump, calcium pump, proton pump
F-ATPase: mitochondrial ATP synthase, chloroplast ATP synthase
V-ATPase: vacuolar ATPase
ABC (ATP binding cassette) transporter: MDR, CFTR, etc.
Secondary active transport[edit]
Secondary active transport
In secondary active transport, also known as coupled transport or co-transport, energy is used to transport molecules across a membrane; however, in contrast to primary active transport, there is no direct coupling of ATP; instead it relies upon the electrochemical potential difference created by pumping ions in/out of the cell.[9] Permitting one ion or molecule to move down an electrochemical gradient, but possibly against the concentration gradient where it is more concentrated to that where it is less concentrated increases entropy and can serve as a source of energy for metabolism (e.g. in ATP synthase).
In August 1960, in Prague, Robert K. Crane presented for the first time his discovery of the sodium-glucose cotransport as the mechanism for intestinal glucose absorption.[10] Crane's discovery of cotransport was the first ever proposal of flux coupling in biology.[11][12]
Cotransporters can be classified as symporters and antiporters depending on whether the substances move in the same or opposite directions.
Antiport[edit]
Function of symports and antiports.
In an antiport two species of ion or other solutes are pumped in opposite directions across a membrane. One of these species is allowed to flow from high to low concentration which yields the entropic energy to drive the transport of the other solute from a low concentration region to a high one.
An example is the sodium-calcium exchanger or antiporter, which allows three sodium ions into the cell to transport one calcium out.[13] Many cells also possess calcium ATPases, which can operate at lower intracellular concentrations of calcium and sets the normal or resting concentration of this important second messenger.[14] But the ATPase exports calcium ions more slowly: only 30 per second versus 2000 per second by the exchanger. The exchanger comes into service when the calcium concentration rises steeply or "spikes" and enables rapid recovery.[15] This shows that a single type of ion can be transported by several enzymes, which need not be active all the time (constitutively), but may exist to meet specific, intermittent needs.
Symport[edit]
Symport uses the downhill movement of one solute species from high to low concentration to move another molecule uphill from low concentration to high concentration (against its concentration gradient). Both molecules are transported in the same direction.
An example is the glucose symporter SGLT1, which co-transports one glucose (or galactose) molecule into the cell for every two sodium ions it imports into the cell.[16] This symporter is located in the small intestines,[17] heart,[18] and brain.[19] It is also located in the S3 segment of the proximal tubule in each nephron in the kidneys.[20] Its mechanism is exploited in glucose rehydration therapy[21] and defects in SGLT2 prevent effective reabsorption of glucose, causing familial renal glucosuria.[22]
Examples[edit]
Metal ions, such as Na+, K+, Mg2+, or Ca2+, require ion pumps or ion channels to cross membranes and distribute through the body
The pump for sodium and potassium is called sodium-potassium pump or Na +/K+-ATPase
In the epithelial cells of the stomach, gastric acid is produced by hydrogen potassium ATPase, an electroneutral pump[citation needed]
Water, ethanol, and chloroform exemplify simple molecules that do NOT require active transport to cross a membrane.
Endocytosis and exocytosis[edit]
Main articles: Endocytosis and Exocytosis
Endocytosis and exocytosis are both forms of bulk transport that move materials into and out of cells, respectively, via vesicles.[23] In the case of Endocytosis, the cellular membrane folds around the desired materials outside the cell.[24] The ingested particle becomes trapped within a pouch, known as a vesicle, inside the cytoplasm. Often enzymes from lysosomes are then used to digest the molecules absorbed by this process.
Biologists distinguish two main types of endocytosis: pinocytosis and phagocytosis.[25]
In pinocytosis, cells engulf liquid particles (in humans this process occurs in the small intestine, where cells engulf fat droplets).[26]
In phagocytosis, cells engulf solid particles.[27]
See also[edit]
ATP-binding cassette transporter
Countercurrent exchange
Protein targeting
Translocation
References[edit]
Jump up ^ "The importance of homeostasis". Science. me. Retrieved 23 April 2013.
Jump up ^ Du Bois-Reymond, E. (1848–84). Untersuchungen über thierische Elektricität Berlin: Reimer. (Vol. 1, Part 1, 1848; Vol. 1, Part 2, 1849; Vol. 2, Part 1, 1860; Vol. 2, Part 2, 1884).
Jump up ^ Rosenberg, T. (1948). On accumulation and active transport in biological systems. I. Thermodynamic considerations. Acta Chem. Scand. 2, 14-33, [1].
Jump up ^ Active Transport Process. Buzzle.com (2010-05-14). Retrieved on 2011-12-05.
Jump up ^ Active Transport Archived August 24, 2011, at the Wayback Machine.. Biologycorner.com. Retrieved on 2011-12-05.
Jump up ^ Physiology: 7/7ch05/7ch05p11 - Essentials of Human Physiology
Jump up ^ Reese, Jane B.; Urry, Lisa A.; Cain, Michael L.; Wasserman, Steven A.; Minorsky, Peter V.; Jackson, Robert B. (2014). Tenth Edition, Campbell's Biology. United States: Pearson Education Inc. p. 135. ISBN 978-0-321-77565-8 – via Tenth edition.
Jump up ^ Cooper, Geoffrey (2009). The Cell: A Molecular Approach. Washington, DC: ASM PRESS. p. 65. ISBN 9780878933006.
Jump up ^ Physiology: 7/7ch05/7ch05p12 - Essentials of Human Physiology
Jump up ^ Crane, Robert K.; Miller, D.; Bihler, I. (1961). "The restrictions on possible mechanisms of intestinal transport of sugars". In Kleinzeller, A.; Kotyk, A. Membrane Transport and Metabolism. Proceedings of a Symposium held in Prague, August 22–27, 1960. Prague: Czech Academy of Sciences. pp. 439–449.
Jump up ^ Wright EM, Turk E (February 2004). "The sodium/glucose cotransport family SLC5". Pflügers Arch. 447 (5): 510–8. PMID 12748858. doi:10.1007/s00424-003-1063-6. Crane in 1961 was the first to formulate the cotransport concept to explain active transport [7]. Specifically, he proposed that the accumulation of glucose in the intestinal epithelium across the brush border membrane was coupled to downhill Na+
transport cross the brush border. This hypothesis was rapidly tested, refined and extended [to] encompass the active transport of a diverse range of molecules and ions into virtually every cell type.
Jump up ^ Boyd CA (March 2008). "Facts, fantasies and fun in epithelial physiology". Exp. Physiol. 93 (3): 303–14. PMID 18192340. doi:10.1113/expphysiol.2007.037523. p. 304. “the insight from this time that remains in all current text books is the notion of Robert Crane published originally as an appendix to a symposium paper published in 1960 (Crane et al. 1960). The key point here was 'flux coupling', the cotransport of sodium and glucose in the apical membrane of the small intestinal epithelial cell. Half a century later this idea has turned into one of the most studied of all transporter proteins (SGLT1), the sodium–glucose cotransporter.
Jump up ^ Yu, SP; Choi, DW (June 1997). "Na(+)-Ca2+ exchange currents in cortical neurons: concomitant forward and reverse operation and effect of glutamate.". The European Journal of Neuroscience. 9 (6): 1273–81. PMID 9215711. doi:10.1111/j.1460-9568.1997.tb01482.x.
Jump up ^ Strehler, EE; Zacharias, DA (January 2001). "Role of alternative splicing in generating isoform diversity among plasma membrane calcium pumps.". Physiological reviews. 81 (1): 21–50. PMID 11152753.
Jump up ^ Patterson, M; Sneyd, J; Friel, DD (January 2007). "Depolarization-induced calcium responses in sympathetic neurons: relative contributions from Ca2+ entry, extrusion, ER/mitochondrial Ca2+ uptake and release, and Ca2+ buffering.". The Journal of General Physiology. 129 (1): 29–56. PMC 2151609  . PMID 17190902. doi:10.1085/jgp.200609660.
Jump up ^ Wright, EM; Loo, DD; Panayotova-Heiermann, M; Lostao, MP; Hirayama, BH; Mackenzie, B; Boorer, K; Zampighi, G (November 1994). "'Active' sugar transport in eukaryotes.". The Journal of Experimental Biology. 196: 197–212. PMID 7823022.
Jump up ^ Dyer, J; Hosie, KB; Shirazi-Beechey, SP (July 1997). "Nutrient regulation of human intestinal sugar transporter (SGLT2) expression.". Gut. 41 (1): 56–9. PMC 1027228  . PMID 9274472. doi:10.1136/gut.41.1.56.
Jump up ^ Zhou, L; Cryan, EV; D'Andrea, MR; Belkowski, S; Conway, BR; Demarest, KT (1 October 2003). "Human cardiomyocytes express high level of Na+/glucose cotransporter 1 (SGLT2).". Journal of cellular biochemistry. 90 (2): 339–46. PMID 14505350. doi:10.1002/jcb.10631.
Jump up ^ Poppe, R; Karbach, U; Gambaryan, S; Wiesinger, H; Lutzenburg, M; Kraemer, M; Witte, OW; Koepsell, H (July 1997). "Expression of the Na+-D-glucose cotransporter SGLT1 in neurons.". Journal of Neurochemistry. 69 (1): 84–94. PMID 9202297. doi:10.1046/j.1471-4159.1997.69010084.x.
Jump up ^ Wright EM (2001). "Renal Na+-glucose cotransporters". Am J Physiol Renal Physiol. 280 (1): F10–8. PMID 11133510.
Jump up ^ Loo, DD; Zeuthen, T; Chandy, G; Wright, EM (12 November 1996). "Cotransport of water by the Na+/glucose cotransporter.". Proceedings of the National Academy of Sciences of the United States of America. 93 (23): 13367–70. PMC 24099  . PMID 8917597. doi:10.1073/pnas.93.23.13367.
Jump up ^ Wright EM, Hirayama BA, Loo DF (2007). "Active sugar transport in health and disease". Journal of internal medicine. 261 (1): 32–43. PMID 17222166. doi:10.1111/j.1365-2796.2006.01746.x.
Jump up ^ Reece, Jane; Urry, Lisa; Cain, Michael; Wasserman, Steven; Minorsky, Peter; Jackson, Robert (2014). Tenth Addition Campbell Biology. United States of America: Pearson Education, Inc. p. 137. ISBN 978-0-321-77565-8 – via Tenth Addition.
Jump up ^ Transport into the Cell from the Plasma Membrane: Endocytosis – Molecular Biology of the Cell – NCBI Bookshelf. Ncbi.nlm.nih.gov (2011-10-03). Retrieved on 2011-12-05.
Jump up ^ Cell : Two Major Process in Exchange Of Materials Between Cell And Environment Archived August 11, 2010, at the Wayback Machine.. Takdang Aralin (2009-10-26). Retrieved on 2011-12-05.
Jump up ^ Pinocytosis: Definition. biology-online.org
Jump up ^ Phagocytosis. Courses.washington.edu. Retrieved on 2011-12-05.
Notes[edit]
Lodish H.; Berk A.; Zipursky S.L.; Matsudaira P.; Baltimore D.; Darnell J. (2000). "Section 15.6 Cotransport by Symporters and Antiporters". Molecular Cell Biology (4th ed.). New York: W.H. Freeman. ISBN 0-7167-3136-3.
External links[edit]
Secondary Active Transport
[hide]
v
t
e
Membrane transport
Mechanisms for chemical transport through biological membranes
Passive transport
Simple diffusion (or non-mediated transport)
Facilitated diffusion
Osmosis
Channels
Carriers
Active transport
Uniporter
Symporter
Antiporter
Primary active transport
Secondary active transport
Cytosis
Endocytosis
Efferocytosis
Non-specific, adsorptive pinocytosis
Phagocytosis
Pinocytosis
Potocytosis
Receptor-mediated endocytosis
Transcytosis
Exocytosis
Degranulation
Authority control
NDL: 00570452
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