Evaluation Of Planetary Boundary Layer Height And PM_2.5 Concentration And The Interrelationship Of Long-term Characteristics Based On Reanalysis Datasets

The rapid development of economy and the acceleration of urbanization and industrialization have caused a significant increase in the emission of atmospheric pollutants.Planetary boundary layer height?PBLH?is a key parameter that directly affects the vertical distribution of atmospheric pollutants.Therefore,studying the relationship between long-term variations of boundary layer height and PM_2.5concentration can help us to understand the impact of changes in the vertical diffusion capacity of the atmosphere from a climatological perspective.In this paper,we evaluated the four reanalysis data of PBLH and PM_2.5 concentrations based on the PBLH data derived from the Integrated Global Radiosonde Archive?IGRA?and PM_2.5concentration monitoring datasets,then systematically analyzed the spatial distribution and long-term variation characteristics of PBLH and PM_2.5 concentration in China over the past 40 years.The main conclusions are as follows:?1?The spatial distributions of the annual and the seasonal mean values of global PBLH calculated from the four reanalysis data at 00:00UTC and 12:00UTC is consistent with IGRA,and the correlation between all the reanalysis data and IGRA is remarkable in Eurasia.However,the PBLH results of four reanalysis data were underestimate than that of IGRA in the whole experiment period,especially in30°N⁶0°N Eurasia at 00:00 and in North America at 12:00.Among them,the PBLH from CFSR,CERA-20C and ERA-Interim were 40-60%underestimate than that of IGRA,Compared to other three reanalysis data,MERRA2 was 20%-40%underestimate,also has smaller bias,relative deviation and root mean square error,which was the closest to the IGRA.It indicated that MERRA2 suitable for the study of PBLH on China region.?2?MERRA2 results can represent the seasonal variation characteristics and the spatial distribution of PM_2.5 concentration in China region,especially got the most accuracy in summer.But the results in some local region have great seasonal differences.Compared with the measured PM_2.5 concentration in southern China,MERRA2 has smaller bias and root mean square error of spring,autumn and winter.The annual and monthly variation characteristics are also close.However,the differences were larger in northern and central China.Due to the small daily variation range of MERRA2,the performance of peaks in diurnal PM_2.5 concentration from MERRA2 dataset is not obvious.A comparison of PM_2.5 concentration air quality levels showed that the deviation of the MERRA2 PM_2.5 increased gradually with increasing pollution levels.?3?The PBLH variation from 1980 to 2018 shows obvious regional characteristics.The distribution are higher in the west and lower in the east except for the northern part of Xinjiang,especially the Taklamakan Desert in the northwest region is higher than other regions in spring and summer.In Each generation,the PBLH also higher in the west and lower in the east.The PBLH in the east of china decreased year by year.In spring and summer,northwest China showed an upward trend,while other regions showed a downward trend.In autumn and winter,eastern China,central China and south China showed a downward trend.From different periods,PBLH of different regions mainly increased in the 1980s.In northwest China,PBLH maintained a rising trend in the 1990s and 2000s.But PBLH in other regions turned downward after the 1990s.It is worth mentioning that,the PBLH increased significantly in the spring of each decade.?4?From 1980 to 2018,the spatial distributions of PM_2.5 concentration is the highest in Taklamakan Desert region,followed by the eastern region in China.In addition,the northwestern region has a high value in the Taklamakan Desert in spring,summer and autumn,while the eastern region showed high value in the winter and low value in the summer.The eastern region showed a significant upward trend in all seasons with the weakest in summer and strongest in winter.In terms of the characteristics of interdecadal changes,there is no significant difference in the distribution of PM_2.5 concentration in northwest China,while in eastern China it increases by year.Except in the eastern region in 2010s,the concentration of PM_2.5maintained an increasing trend in each generation.Besides,before 2010s,the concentration of PM_2.5 in each generation showed a significant increasing trend in all seasons,and then turned to a significant decreasing trend.?5?There are obvious differences in the long-term relationship between PBLH and PM_2.5 concentration in different regions.The relationship shows obvious negative correlation in east,central and south China,and the negative correlation becomes stronger after 2000.In some periods,the relationship shows a negative correlation between north China and northeast China.But the relationship showed positive correlation in northwest China.In terms of spatial distribution,the eastern region with relatively flat terrain and lower elevation showed obvious negative correlation,while the western region with higher elevation showed positive correlation.According to the analysis of the relationship between PBLH and PM_2.5 components,all PM_2.5components in the western region shows a positive correlation with PBLH,while the eastern region showed a negative correlation except the dust component.Based on the Coefficients of determination of PBLH and PM_2.5 concentration,the contribution rate of PBLH in eastern China reaches 42%,which has a great influence on PM_2.5concentration change in eastern China.