Impacts of AOD Correction and Spatial Scale on the Correlation between High-Resolution AOD from Gaofen-1 Satellite and In Situ PM2.5 Measurements in Shenzhen City, China

Abstract

Satellite-derived aerosol optical depth (AOD) is widely used to estimate surface PM2.5 concentrations. Most AOD products have relatively low spatial resolutions (i.e., ≥1 km). Consequently, insufficient research exists on the relationship between high-resolution (i.e., <1 km) AOD and PM2.5 concentrations. Taking Shenzhen City, China as the study area, we derived AOD at the 16-m spatial resolution for the period 2015–2017 based on Gaofen-1 (GF-1) satellite images and the Dark Target (DT) algorithm. Then, we extracted AOD at spatial scales ranging from 40 m to 5000 m and applied vertical and humidity corrections. We analyzed the correlation between AOD and PM2.5 concentrations, and the impacts of AOD correction and spatial scale on the correlation. It was found that the DT-derived GF-1 AOD at different spatial scales had statistically significant correlations with surface PM2.5 concentrations, and the AOD corrections strengthened the correlations. The correlation coefficients (R) between AOD at different spatial scales and PM2.5 concentrations were 0.234–0.329 and 0.340–0.423 before and after AOD corrections, respectively. In spring, summer, autumn, and winter, PM2.5 concentrations had the best correlations with humidity-corrected AOD, uncorrected AOD, vertical and humidity-corrected AOD, and uncorrected AOD, respectively, indicating a distinct seasonal variation of the aerosol characteristics. At spatial scales of 1–5 km, AOD at finer spatial scales generally had higher correlations with PM2.5 concentrations. However, at spatial scales <1 km, the correlations fluctuated irregularly, which could be attributed to scale mismatches between AOD and PM2.5 measurements. Thus, 1 km appears to be the optimum spatial scale for DT-derived AOD to maximize the correlation with PM2.5 concentrations. It is also recommended to aggregate very high-resolution DT-derived AOD to an appropriate medium resolution (e.g., 1 km) before matching them with in situ PM2.5 measurements in regional air pollution studies.

Influence of Spatial Resolution and Retrieval Frequency on Applicability of Satellite-Predicted PM2.5 in Northern China

“…Compared with the remarkable influence of sampling frequency, the difference in spatial resolution mainly impacts the consistence of MODIS PM 2.5 results in detailed scales (Figure 7), which is important for exposure assessment on a regional scale such as the BTH. Most previous studies focus on influence of spatial resolution on AOD-PM 2.5 relationship [23][24][25][26]. It is found that correlation of AOD-PM 2.5 gets slightly higher for high-resolution PM 2.5 estimation in the megacity of Beijing in northern China [31], but is not obvious on a regional scale (Figures 5 and 6).…”

“…Thus, whether satellite PM 2.5 can capture the temporal variations and actual magnitude of PM 2.5 in northern China can be obviously be impacted by the sampling frequency of satellite AOD. However, previous studies mainly focused on the influence of satellite AOD parameters such as spatial resolution on modeling of the AOD-PM 2.5 relationship [23][24][25][26]. Even the several widely used MODIS aerosol products have remarkable differences in sampling frequency and spatial resolution [17][18][19].…”

Influence of Spatial Resolution on Satellite-Based PM2.5 Estimation: Implications for Health Assessment

“…Additionally, after applying vertical and humidity corrections of AOD following previous works [57,58], the spatial resolution effect on the AOD-PM 2.5 correlation still holds (not shown). Note that the spatial resolution range may affect the sensitivity of AOD-PM 2.5 correlation on resolution.…”

“…Note that the spatial resolution range may affect the sensitivity of AOD-PM 2.5 correlation on resolution. For instance, Wu et al [57] found that, as degrading spatial resolution, the correlation in Shenzhen City in summer rapidly increases until reaching the peak at about 1 km resolution and then slowly decreases when going to coarser resolutions.…”

Spatial distribution of aerosol optical depth over India during COVID-19 lockdown phase-1

“…MODIS has been widely used for the AOD estimation over land and ocean since early 2000 [ 16 , 17 , 19 – 22 ]. Variation of AOD over India has also been extensively studied using MODIS aerosol data [ 18 , 23 – 25 ]. Moreover, all the above-mentioned research works have been conducted under the usual natural conditions without any restrictions on anthropogenic activities.…”