Environmental quality not only impacts public health but is also closely related to the sustainable development of the economy. Air quality constitutes a crucial domain in China's environmental governance. Its perceptibility in daily life directly affects people's production and living activities, while also being intricately linked to economic environments, corporate operations, and profitability. Urban high-quality development is increasingly constrained by air quality conditions, as continuous increases in energy consumption and environmental deterioration during economic growth can hinder development and degrade economic performance.
The Air Quality Index (AQI) is China's current nonlinear dimensionless index for quantitatively assessing air quality conditions, primarily used to characterize short-term urban air quality status and trends. Its hierarchical calculation references the national standard GB 3095-2012 "Ambient Air Quality Standards" (current version, latest revision 2012). The pollutants evaluated include SO2, NO2, PM10, PM2.5, O3, and CO, with hourly updates.
Air quality assessment relies on fixed-point, continuous, or timed sampling, measurement, and analysis of atmospheric pollutants conducted by urban air quality monitoring stations. These stations are strategically distributed across urban built-up areas to ensure uniform coverage. The final AQI is calculated as the arithmetic mean of pollutant concentrations from all monitoring points, representing the overall average concentration in urban built-up areas. Therefore, monitoring station data serves as primary data for air quality evaluation, with station locations significantly influencing assessment outcomes.
Given the rapid dispersion of air pollutants, quick responsiveness to control measures, and the availability of daily data, air quality data is frequently utilized in empirical research. The CnOpenData platform provides both daily urban air quality data and comprehensive location-specific monitoring station data, collecting complete records since May 13, 2014. This offers researchers a complete and reliable data source for air quality studies.
Time Coverage
Monitoring data available from May 13, 2014
Field Description
Monitoring Station List
Urban Air Quality Table
Station Air Quality Table
Sample Data
Monitoring Station List
Urban Air Quality Table
Station Air Quality Table
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.
- 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, R.B., Zhao, Q., Wang, L.Y., 2019, “Natural Resource Asset Departure Audit and Air Pollution Control: 'Harmonious Championship' or 'Environmental Qualification Competition'”, China Industrial Economics, No. 10.
- Shen, Y.J., Yu, S.L., Jiang, D.Q., 2019, “Can Air Quality Improvement Reduce Corporate Labor Costs?”, Management World, No. 6.
- Sun, C.W., Luo, Y., Yao, X., 2019, “Transport Infrastructure and Urban Air Pollution: Empirical Evidence from China”, Economic Research Journal, No. 8.
- Chen, S., Chen, T., 2014, “Air Quality and Public Health: Evidence from Sulfur Dioxide Emissions of Thermal Power Plants”, Economic Research Journal, No. 8.
- Guo, F., Shi, Q.L., 2017, “Official Turnover, Collusion Deterrence, and Temporary Air Quality Improvement”, Economic Research Journal, No. 7.
- Luo, Z., Li, H.R., 2018, “The Impact of 'Air Pollution Prevention and Control Action Plan' on Air Quality”, China Industrial Economics, No. 9.
Data Update Frequency
Annual Update