生态与环境数据
Please enter the keyword
Back

Introduction to air quality site monitoring data

 Environmental quality not only affects public health, but is also closely related to sustainable economic development. Air quality is an important area of ​​environmental governance in my country. It is highly perceptible in daily life and directly affects people's daily production and life. It is also closely related to the economic environment, corporate development and profitability. High-quality urban development is increasingly affected by urban air quality. Constraints, the continued rise in energy consumption in economic development and the intensification of environmental degradation will restrict economic development and reduce the quality of economic development.

  The Air Quality Index (AQI) is a nonlinear dimensionless index currently used in my country to quantitatively describe air quality conditions. It is suitable for expressing the short-term air quality conditions and changing trends of cities. The reference standard for index classification calculation is GB 3095-2012 "Ambient Air Quality Standard" (current, latest revised in 2012), and the pollutants participating in the evaluation are SO2, NO2, PM10, PM2.5, O3, CO etc. The publishing frequency is once every hour.

  The assessment of air quality is based on relevant data obtained by urban air quality monitoring stations through fixed-point, continuous or regular sampling, measurement and analysis of pollutants present in the atmosphere and air. Air quality monitoring stations are located in the built-up areas of each city and are relatively evenly distributed, covering all built-up areas. The final air quality index is calculated from the arithmetic mean of the pollutant concentrations at all monitoring points in the city, representing The overall average concentration of pollutants in the built-up area of ​​the city. Therefore, air quality station monitoring data is the first-hand data for assessing air quality, and the location of air quality monitoring stations will also affect the assessment of air quality.

  Air quality data are often used in empirical research due to the rapid dissipation of air pollutants, rapid response to treatment measures, and the availability of daily data. The data of the CnOpenData platform includes daily data on air quality in each city, as well as location information and monitoring data of each monitoring station. All information since May 13, 2014 has been collected to provide air quality information. Quality related research provides a complete and reliable source of data.

Time interval

Monitoring time starts from 2014.05.13

Field display

Monitoring site list

Chinese field Chinese definition of fields
Monitoring point coding Monitoring point coding
Monitoring point name Monitoring point name
City City
Longitude Longitude
Latitude Latitude

Urban air quality table

Chinese field display Chinese definition of field
date Data collection date
hour Data collection time
City Data collection city
AQI Air quality index
PM2.5 1 hour average of particulate matter (particle size less than or equal to 2.5μm)
PM2.5_24h 24-hour sliding average of particulate matter (particle size less than or equal to 2.5 μm)
PM10 One-hour average value of particulate matter (particle size less than or equal to 10 μm)
PM10_24h 24-hour sliding average of particulate matter (particle size less than or equal to 10 μm)
SO2 1-hour average value of sulfur dioxide
SO2_24h 24-hour sliding average of sulfur dioxide
NO2 1-hour average value of nitrogen dioxide
NO2_24h 24-hour sliding average of nitrogen dioxide
O3 Ozone 1 hour average value
O3_24h Ozone daily maximum 1-hour average value
O3_8h Ozone 8-hour sliding average
O3_8h_24h Ozone daily maximum 8-hour moving average
CO One hour average of carbon monoxide
CO_24h 24-hour sliding average of carbon monoxide

Site air quality table

Chinese field display Chinese definition of field
date Data collection date
hour Data collection time
site Data collection site
AQI Air quality index
PM2.5 1 hour average of particulate matter (particle size less than or equal to 2.5μm)
PM2.5_24h 24-hour sliding average of particulate matter (particle size less than or equal to 2.5 μm)
PM10 One-hour average value of particulate matter (particle size less than or equal to 10 μm)
PM10_24h 24-hour sliding average of particulate matter (particle size less than or equal to 10 μm)
SO2 1-hour average value of sulfur dioxide
SO2_24h 24-hour sliding average of sulfur dioxide
NO2 1-hour average value of nitrogen dioxide
NO2_24h 24-hour sliding average of nitrogen dioxide
O3 Ozone 1 hour average value
O3_24h Ozone daily maximum 1-hour average value
O3_8h Ozone 8-hour sliding average
O3_8h_24h Ozone daily maximum 8-hour moving average
CO One hour average of carbon monoxide
CO_24h 24-hour sliding average of carbon monoxide

Sample data

Detection site list

Monitoring point coding Monitoring point name City Longitude Latitude
1001A Wanshou West Palace Beijing 116.366 39.8673
1002A Dingling Beijing 116.17 40.2865
1003A 东四 Beijing 116.434 39.9522
1004A Temple of Heaven Beijing 116.434 39.8745
1005A Agricultural Exhibition Hall Beijing 116.473 39.9716
1006A Guan Yuan Beijing 116.361 39.9425
1007A Wanliu, Haidian District Beijing 116.315 39.9934
1008A Shunyi New Town Beijing 116.72 40.1438
1009A Huairou Town Beijing 116.644 40.3937
1010A Changping Town Beijing 116.23 40.1952
1011A Olympic Sports Center Beijing 116.407 40.0031
1012A Ancient City Beijing 116.225 39.9279
1013A Municipal Monitoring Center Tianjin 117.151 39.097
1014A Nankou Road Tianjin 117.193 39.173
1015A Qinjian Road Tianjin 117.145 39.1654
1016A Nanjing Road Tianjin 117.184 39.1205
1017A Dazhigu No. 8 Road Tianjin 117.237 39.1082
1018A The way forward Tianjin 117.202 39.0927
1019A Beichen Science and Technology Park Tianjin 117.1837 39.2133
1020A Tianshan Road Tianjin 117.269 39.1337
1021A Yuejin Road Tianjin 117.307 39.0877
1023A Fourth Street Tianjin 117.707 39.0343
1024A Yongming Road Tianjin 117.457 38.8394
1025A Aerospace Road Tianjin 117.401 39.124
1026A Hanbei Road Tianjin 117.764 39.1587
1027A Tuanbowa Tianjin 117.157 38.9194
1028A Chemical Engineering School Shijiazhuang
1029A Staff Hospital Shijiazhuang 114.4548 38.0513
1030A High-tech Zone Shijiazhuang 114.6046 38.0398
1031A Northwestern Water Source Shijiazhuang 114.5019 38.1398
1032A Southwestern Higher Education Shijiazhuang 114.4586111 38.00583333
1033A Century Park Shijiazhuang 114.5330556 38.01777778
1034A People's Hall Shijiazhuang 114.5214 38.0524
1035A Fenglong Mountain Shijiazhuang 114.3541 37.9097
1036A Supply and Marketing Cooperative Tangshan 118.1662 39.6308
1037A Radar station Tangshan 118.144 39.643
1038A Materials Bureau Tangshan 118.1853 39.6407
1039A Ceramic Company Tangshan 118.2185 39.6679
1040A Twelve Middle School Tangshan 118.1838 39.65782
1041A Hill Tangshan 118.1997 39.6295
1042A Beidaihe Environmental Protection Bureau Qinhuangdao 119.5259 39.8283
1043A First level Qinhuangdao 119.7624 40.0181
1044A Monitoring station Qinhuangdao 119.6023 39.9567
1045A City Hall Qinhuangdao 119.607 39.9358
1046A Construction Building Qinhuangdao 119.5369 39.9419
1047A Environmental Protection Bureau Handan 114.5129 36.61763
1048A East Sewage Treatment Plant Handan 114.5426 36.6164
1049A Mining Institute Handan 114.5035 36.5776
1050A Congtai Park Handan 114.4965 36.61981

Urban air quality table

date hour City AQI PM2.5 PM2.5_24h PM10 PM10_24h SO2 SO2_24h NO2 NO2_24h O3 O3_24h O3_8h O3_8h_24h CO CO_24h
20140513 0 三亚 36 25 19 33 33 2 2 13 14 49 71 52 61 0.5 0.51
20140513 0 三门峡 95 48 48 140 117 26 29 37 25 4 134 42 98 1.25 1.15
20140513 0 上海 109 82 83 116 103 18 23 73 56 88 206 123 169 0.88 1.02
20140513 0 东莞 99 74 46 127 69 23 16 79 57 7 100 32 74 1.61 0.93
20140513 0 东营 123 86 49 196 111 167 75 114 38 29 176 96 149 1.62 0.84
20140513 0 中山 57 30 63 64 88 8 12 34 38 7 69 33 45 1.7 1.36
20140513 0 临安 114 86 49 155 108 21 12 43 31 59 121 82 102 0.84 0.83
20140513 0 临汾 125 95 72 170 116 50 77 43 37 33 110 61 93 2.75 2.99
20140513 0 临沂 119 73 56 188 148 79 62 104 57 11 94 44 82 1.69 1.09
20140513 0 丹东 106 80 38 125 64 17 19 39 25 92 134 101 123 2.04 1.44
20140513 0 丽水 32 19 16 32 29 5 6 24 28 50 99 64 88 0.64 0.81
20140513 0 义乌 73 53 44 86 63 50 22 56 31 27 159 58 144 1.11 0.87
20140513 0 乌鲁木齐 113 41 32 175 131 14 17 85 45 11 69 42 57 1.08 0.66
20140513 0 九江 71 44 30 92 67 23 22 34 27 24 69 46 64 0.73 0.75
20140513 0 乳山 69 50 32 54 48 12 18 17 16 89 159 108 151 0.95 0.85
20140513 0 云浮 56 39 23 62 33 12 15 18 15 7 19 8 12 2.97 2.39
20140513 0 佛山 88 65 57 120 83 31 31 102 76 8 175 37 65 1.85 1.47
20140513 0 保定 91 52 34 132 112 40 29 29 27 48 135 94 108 1.28 1.07
20140513 0 克拉玛依 58 24 19 65 54 4 4 5 5 86 111 87 100 0.88 1.24
20140513 0 兰州 64 37 59 78 119 35 53 50 69 50 148 76 112 1.19 1.85
20140513 0 包头 140 44 43 229 164 31 55 94 54 15 147 77 133 1.31 1.14
20140513 0 北京 81 49 35 112 73 18 8 56 45 71 145 105 128 0.71 0.68
20140513 0 北海 61 41 16 72 48 13 17 11 11 87 154 108 133 1.57 1.69
20140513 0 南京 109 62 67 168 137 16 25 118 63 16 198 80 174 0.98 1.03
20140513 0 南充 141 108 94 148 135 17 26 33 31 40 110 40 56 0.94 0.83
20140513 0 南宁 73 53 35 96 80 9 20 48 40 61 142 97 123 1.47 1.33
20140513 0 南昌 92 49 36 133 71 13 21 73 32 15 116 55 105 1.47 1.04
20140513 0 南通 111 84 92 163 138 63 68 95 74 46 189 86 157 0.82 1.47
20140513 0 即墨 94 70 43 130 79 71 37 98 45 38 140 73 129 0.9 0.69
20140513 0 厦门 31 18 19 31 28 19 20 55 49 30 89 48 62 0.4 0.76
20140513 0 句容 83 61 72 85 65 43 43 47 36 75 255 136 193 0.87 1.19
20140513 0 台州 78 57 49 67 57 8 6 32 33 35 110 55 97 0.95 0.98
20140513 0 合肥 93 62 52 136 105 15 13 45 27 18 66 28 55 1.13 0.77
20140513 0 吉林 32 9 13 16 24 5 6 9 17 103 110 87 103 1.06 1.16
20140513 0 吴江 92 66 48 133 87 55 32 62 31 63 146 94 139 1.11 0.82
20140513 0 呼和浩特 98 54 38 145 114 58 39 68 53 21 76 43 62 2.26 2.02
20140513 0 咸阳 83 44 43 115 134 37 40 76 57 30 109 73 88 1.15 1.16
20140513 0 哈尔滨 33 23 25 22 34 8 10 19 38 74 84 65 69 0.51 0.62
20140513 0 唐山 82 55 40 113 80 19 16 48 38 80 169 121 149 0.67 0.79
20140513 0 嘉兴 139 106 60 153 82 19 27 45 45 80 166 94 140 0.98 0.96
20140513 0 嘉峪关 52 12 24 53 97 33 47 28 29 120 171 146 162 1.1 0.9
20140513 0 大同 97 56 38 143 101 26 36 60 36 41 86 58 80 1.36 2.22
20140513 0 大庆 30 21 29 23 38 9 9 10 16 80 83 70 74 0.37 0.4
20140513 0 大连 50 30 37 50 55 8 7 36 39 86 108 83 95 0.72 0.9
20140513 0 天津 69 44 43 87 76 23 24 53 40 51 125 85 105 1.03 1.39
20140513 0 太仓 106 80 80 114 108 39 61 46 33 119 153 129 139 1.21 1.32
20140513 0 太原 155 102 63 260 155 61 59 116 62 10 111 62 98 1.61 1.18
20140513 0 威海 51 27 31 51 57 20 27 17 28 124 177 109 135 0.5 0.66
20140513 0 宁波 58 41 46 66 62 18 37 60 38 68 297 111 163 1.04 1.23
20140513 0 安阳 81 50 64 111 122 66 32 78 58 51 144 103 134 0.9 1.2

Site air quality table

date hour site AQI PM2.5 PM2.5_24h PM10 PM10_24h SO2 SO2_24h NO2 NO2_24h O3 O3_24h O3_8h O3_8h_24h CO CO_24h
20140513 0 1001A 73 41 34 96 73 17 5 42 45 92 155 111 137 0.7 0.738
20140513 0 1002A 32 22 28 60 2 4 23 20 63 143 106 129 0.2 0.221
20140513 0 1003A 84 54 36 118 74 20 8 39 42 86 151 113 136 0.7 0.788
20140513 0 1004A 67 39 31 84 60 22 7 29 37 88 154 84 127 0.6 0.686
20140513 0 1005A 75 47 36 100 78 20 7 42 52 107 176 130 155 0.6 0.675
20140513 0 1006A 83 56 34 115 73 19 8 59 53 77 162 119 146 0.9 0.726
20140513 0 1007A 102 61 38 153 86 17 10 72 56 48 130 94 121 0.7 0.7
20140513 0 1008A 82 59 41 113 74 15 6 76 45 50 155 107 135 0.8 0.636
20140513 0 1009A 25 40 3 24 76 76 0.691
20140513 0 1010A 68 32 32 86 69 3 5 41 33 59 144 95 119 0.5 0.575
20140513 0 1011A 90 55 41 130 85 20 9 58 53 67 147 105 126 0.6 0.596
20140513 0 1012A 86 47 35 121 89 24 18 97 55 36 142 95 126 1 0.629
20140513 0 1013A 77 56 57 71 88 24 21 33 35 66 136 100 121 0.117 0.774
20140513 0 1014A 72 38 41 93 75 19 20 35 40 85 167 128 148 0.936 1.478
20140513 0 1015A 62 35 37 74 65 21 22 29 34 67 134 102 118 1.534 2.072
20140513 0 1016A 67 48 50 76 78 22 19 32 41 72 127 95 117 0.93 1.318
20140513 0 1017A 53 28 33 55 60 28 24 43 39 69 134 101 116 1.052 1.767
20140513 0 1018A 59 67 50 32 19 40 36 61 131 94 120 1.017
20140513 0 1019A 80 45 54 109 106 24 35 39 42 70 145 112 127 0.335 1.302
20140513 0 1020A 83 61 60 64 83 25 22 33 33 80 145 107 131 0.715 1.262
20140513 0 1021A 64 42 45 78 84 17 26 46 40 66 152 109 134 0.631 1.023
20140513 0 1022A 72 42 48 93 85 13 16 33 32 57 108 81 101 1.087 1.356
20140513 0 1023A 76 40 32 102 54 9 23 54 43 11 89 38 63 1.373 1.803
20140513 0 1024A 88 65 58 89 87 28 19 118 48 12 48 36 43 0.797 0.996
20140513 0 1025A 66 37 38 82 94 18 16 42 43 64 127 94 110 0.73 1.114
20140513 0 1026A 86 51 43 122 98 27 26 57 37 51 166 88 115 1.471 1.17
20140513 0 1027A 82 60 44 90 73 23 26 24 19 67 124 94 112 0.916 1.091
20140513 0 1028A 79 58 50 118 74 44 147 48 22 136 74 117 1.139 1.076
20140513 0 1029A 124 58 37 197 125 98 70 113 63 11 151 77 132 1.133 0.825
20140513 0 1030A 100 50 45 150 112 56 40 90 62 9 57 35 46 1 0.81
20140513 0 1031A 131 80 45 212 138 77 60 65 16 170 92 145 0.846 0.603
20140513 0 1032A 144 76 34 238 109 107 56 91 55 6 128 64 113 1.37 1.073
20140513 0 1033A 123 63 36 195 94 72 34 90 49 17 164 81 138 0.61 0.465
20140513 0 1034A 127 80 25 204 85 116 57 98 55 8 115 52 98 0.827 0.613
20140513 0 1035A 80 27 27 110 111 90 86 10 9 145 164 138 140 0.423 0.402
20140513 0 1036A 93 47 41 136 94 15 12 37 33 81 164 125 146 0.538 0.587
20140513 0 1037A 100 75 38 117 83 14 12 59 30 58 179 126 156 0.724 0.554
20140513 0 1038A 90 38 37 130 77 17 16 53 55 98 172 119 146 0.64 0.751
20140513 0 1039A 107 80 37 139 66 46 47 68 56 73 149 106 131 0.516 0.526
20140513 0 1040A 85 58 45 120 87 10 8 37 29 80 162 124 148 0.801 0.772
20140513 0 1041A 69 50 41 83 72 34 28 44 37 83 163 114 147 0.533 1.095
20140513 0 1042A 72 31 30 93 67 39 50 25 33 14 28 20 27 1.352 1.503
20140513 0 1043A 82 22 11 114 64 11 5 48 40 11 57 25 34 1.044 0.874
20140513 0 1044A 40 26 23 40 32 26 30 69 14 43 21 27 1.056 1.062
20140513 0 1045A 67 38 41 83 64 18 21 54 37 65 143 100 118 0.752 0.828
20140513 0 1046A 66 3 6 81 57 29 22 58 24 52 187 115 154 1.313 1.023
20140513 0 1047A 79 52 51 107 157 28 40 42 52 90 158 124 141 0.719 0.995
20140513 0 1048A 98 59 58 146 172 18 40 35 47 69 130 104 118 1.624 1.946
20140513 0 1049A 75 54 62 100 150 41 52 55 63 77 158 118 141 0.9 1.098
20140513 0 1050A 182 137 66 140 35 58 34 47 57 158 119 143 1.038 1.525

Related literature

  • Dong, R., Fisman, R., Wang, Y., and Xu, N.H., 2019, “Air pollution, affect, and forecasting bias: Evidence from Chinese financial analysts”, Journal of Financial Economics, forthcoming.< /li>
  • Huang, J. K., Xu, N. H., and Yu, H.H., 2019, “Pollution and performance: Do investors make worse trades on hazy days?”, Management Science, forthcoming.
  • Huang Rongbing, Zhao Qian, Wang Liyan, 2019: "Natural Resource Assets Off-duty Audit and Air Pollution Prevention: "Harmonious Championship" or "Environmental Protection Qualifying Competition", "China Industrial Economy" Issue 10.
  • Shen Yongjian, Yu Shuangli, Jiang Dequan, 2019: "Can air quality improvement reduce corporate labor costs?", "Management World" Issue 6.
  • Sun Chuanwang, Luo Yuan, and Yao Xin, 2019: "Transportation Infrastructure and Urban Air Pollution - Empirical Evidence from China", "Economic Research" Issue 8.
  • Chen Shuo, Chen Ting, 2014: "Air Quality and Public Health: Taking Sulfur Dioxide Emissions from Thermal Power Plants as an Example", "Economic Research" Issue 8.
  • Guo Feng, Shi Qingling, 2017: "Official Replacement, Collusive Deterrence, and Temporary Improvement of Air Quality", "Economic Research" Issue 7.
  • Luo Zhi, Li Haoran, 2018: "The Impact of the Implementation of the "Ten Atmospheric Policy" on Air Quality", "China Industrial Economy" Issue 9.

Data update frequency

Annual Update

文件下载