Impact of diurnal variability and meteorological factors on the PM2.5 - AOD relationship: Implications for PM2.5 remote sensing

Abstract

PM retrieval from space is still challenging due to the elusive relationship between PM and aerosol optical depth (AOD), which is further complicated by meteorological factors. In this work, we investigated the diurnal cycle of PM in China, using ground-based PM measurements obtained at 226 sites of China Atmosphere Watch Network during the period of January 2013 to December 2015. Results showed that nearly half of the sites witnessed a PM maximum in the morning, in contrast to the least frequent occurrence (5%) in the afternoon when strong solar radiation received at the surface results in rapid vertical diffusion of aerosols and thus lower mass concentration. PM tends to peak equally in the morning and evening in North China Plain (NCP) with an amplitude of nearly twice or three times that in the Pearl River Delta (PRD), whereas the morning PM peak dominates in Yangtze River Delta (YRD) with a magnitude lying between those of NCP and PRD. The gridded correlation maps reveal varying correlations around each PM site, depending on the locations and seasons. Concerning the impact of aerosol diurnal variation on the correlation, the averaging schemes of PM using 3-h, 5-h, and 24-h time windows tend to have larger R biases, compared with the scheme of 1-h time window, indicating diurnal variation of aerosols plays a significant role in the establishment of explicit correlation between PM and AOD. In addition, high cloud fraction and relative humidity tend to weaken the correlation, regardless of geographical location. Therefore, the impact of meteorology could be one of the most plausible alternatives in explaining the varying R values observed, due to its non-negligible effect on MODIS AOD retrievals. Our findings have implications for PM remote sensing, as long as the aerosol diurnal cycle, along with meteorology, are explicitly considered in the future.

A review of current knowledge concerning PM<sub>2. 5</sub> chemical composition, aerosol optical properties and their relationships across China

“…Satellite retrievals of AOD have been widely applied to estimate surface PM 2.5 concentrations using statistical models (Liu et al, 2005;Wang and Christopher, 2003). Although the correlation between AOD and PM 2.5 mass concentration depends on many factors, such as aerosol size distribution, refractive index, single-scattering albedo and meteorological factors Guo et al, 2009bGuo et al, , 2017, the predicted PM 2.5 mass from satellite AOD data compared well with ground-level measurements Xie et al, 2015b). Moreover, the spatial distributions of AOD measured using sun photometers mostly agreed with those retrieved from satellite data (Che et al, 2014Liu et al, 2016b;Pan et al, 2010).…”

The relationships between PM2.5 and aerosol optical depth (AOD) in mainland China: About and behind the spatio-temporal variations

“…Guo et al(Guo et al, 2009) studied the correlation between PM concentration and AOD in 11 PM observation sites from China Atmosphere Watch Network (CAWNET) in eastern China in 2009 and emphasize the importance of spatial variations of PM-AOD relationship with foresights. In their later work in 2017 (Guo et al, 2017a), they studied the spatial variations of PM2.5-AOD relationship over the whole China based on 50km 50km grids and find a strong correlation in North China Plain(0.50<R<0.71) and relatively weaker correlation in PRD and YRD(0.35<R<0.55). But the resolution is quite coarse and some important spatial variation details may have been ignored.…”

Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns

“…Many studies have been published on aerosols in relation to air quality in the eastern part of China, including satellite remote sensing, ground-based measurements, modeling and combinations thereof, which often focus on local or regional aspects (e.g., Song et al, 2009;Ma et al, 2016;Zou et al, 2017;Xue et al, 2017;Miao et al, 2017;Guo et al, 2017). Satellites offer the opportunity to obtain information, using the same instruments and methods, over a large area during a longer period of time.…”