Reconstruction of daily haze data across China between 1961 and 2020. (9th February 2022) - Yu, Yu; Ren, Zhihua; Meng, Xiaoyan
Abstract: Long‐term homogenized haze data are important to understand long‐term changes in air quality. However, there is uncertainty with regard to the trend of haze days due to frequent changes in weather phenomena and visibility observation methods used in China, thereby impairing the understanding of how air quality has varied over time due to global warming. In this study, we analysed historical data on haze days collected by surface weather stations across China and identified several issues in the raw data, including the incorrect identification of floating dust as haze, zero annual records of haze days due to a lack of visibility observations, and incorrect identification of haze as smoke. To correct the affected data, inhomogeneities in the raw annual haze‐day data series since 1980 were resolved by removing floating dust observations from the haze data. Then, automated visibility measurements recorded since 2014 were calibrated according to the percentage of visibility measurements using <10 km as a reference. Finally, based on the corrected and quality‐controlled visibility, relative humidity, and weather data, haze identification was performed to reconstruct daily haze‐day data for China between 1961 and 2020. During this process, automated observation data were homogeneously standardized with former manual observation data. The mean annual haze‐day trends of each region in China showed that the national average number of haze days gradually increased at a rate of 4.27 days per decade between 1961 and 2014, after which it decreased at −1.9 days per year. This trend was verified with the variations in PM2.5 concentrations. Overall, this study presents a novel method for determining the variation and spatial distribution of haze days over the last 60 years in China. The study findings will facilitate future analyses of the spatiotemporal trends of haze days, as well as atmospheric, environmental, and climatic changes over China. Abstract : This study eliminates issues affecting historical haze data in China and calibrates the automatic visibility data using visibility measurements below 10 km. Long‐term homogenized haze‐day data series are reconstructed for China using corrected data. The results facilitate future analyses of the spatiotemporal trends of haze days, as well as atmospheric, environmental, and climatic changes over China.