Quality Control Research Of Air Pollutant Hourly Monitoring Data

Recently, the increasingly frequent air pollution episodes bring great hazard to human life and environment. The well developed monitoring net system and quality control or quality assurance works are the basis of further research. Currently, the research about quality control or quality assurance works of air pollution monitoring data is mainly focus on the standard requirements for monitoring and equipment testing. There are seldom research focusing on the quality check and quality assessment of monitoring data. Based on this situation, we designed a quality control program which containing threshold value test, extreme value test, time consistency test, variable consistency test and visual check. The hourly mass concentration data of 6 air pollutants we used here was published online by Ministry of Environmental Protection of the People’s Republic of China. We chose discordancy test, Hanning filter and robust regression as major outlier detection methods. The quality control code for different data quality has also be designed. After applying this quality program to monitoring data, the data quality of each air pollutant was evaluated. The overall quality standards of air pollutants monitoring data was poor. Generally, PM2.5, PM10, NO2 and O3 monitoring data had relatively good quality, the valid percentage of monitoring hours was between 70% and 90% in most monitoring sites. There were many sites had significant data drifting phenomenon in CO mass concentration data, and the spike like outliers in SO2 data were frequent. The more research on quality control and quality assurance work of air pollutants monitoring data should be done in future.