Abstract
The aerosol optical depth (AOD) represents the light attenuation by aerosols and is an important threat to urban air quality, production activities, human health, and sustainable urban development in arid and semiarid regions. To some extent, the AOD reflects the extent of regional air pollution and is often characterized by significant spatiotemporal dynamics. However, detailed local AOD information is ambiguous at best due to limited monitoring techniques. Currently, the availability of abundant satellite data and constantly updated AOD extraction algorithms offer unprecedented perspectives for high-resolution AOD extraction and long-time series analysis. This study, based on the long-term sequence MOD09A1 data from 2010 to 2018 and lookup table generation, uses the improved deep blue algorithm (DB) to conduct fine-resolution (500 m) AOD (at 550 nm wavelength) remote sensing (RS) estimation on Landsat TM/OLI data from the Urumqi region, analyzes the spatiotemporal AOD variation characteristics in Urumqi and combines gray relational analysis (GRA) and the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to analyze AOD influence factors and simulate pollutant propagation trajectories in representative periods. The results demonstrate that the improved DB algorithm has a high inversion accuracy for continuous AOD inversion at a high spatial resolution in urban areas. The spatial AOD distribution in Urumqi declines from urban to suburban areas, and higher AODs are concentrated in cities and along roads. Among these areas, Xinshi District has the highest AOD, and Urumqi County has the lowest AOD. The seasonal AOD variation characteristics are distinct, and the AOD order is spring (0.411) > summer (0.285) > autumn (0.203), with the largest variation in spring. The average AOD in Urumqi is 0.187, and the interannual variation generally shows an upward trend. However, from 2010 to 2018, AOD first declined gradually and then declined significantly. Thereafter, AOD reached its lowest value in 2015 (0.076), followed by a significant AOD increase, reaching a peak in 2016 (0.354). This shows that coal to natural gas (NG) project implementation in Urumqi promoted the improvement of Urumqi’s atmospheric environment. According to GRA, the temperature has the largest impact on the AOD in Urumqi (0.699). Combined with the HYSPLIT model, it was found that the aerosols observed over Urumqi were associated with long-range transport from Central Asia, and these aerosols can affect the entire northern part of China through long-distance transport.
Highlights
An aerosol is a general term for the solid or liquid particles suspended in the atmosphere with a diameter of 10−3–102 μm [1,2]
To verify the aerosol optical depth (AOD) estimation using the improved deep blue algorithm (DB) algorithm in typical cities in arid areas, field monitoring data from handheld sunphotometer and Aerosol Robotic Network (AERONET) are used for accuracy verification; comparison with Moderate Resolution Imaging Spectroradiometer (MODIS) DB aerosol products (MYD04 C6) is performed (Figure 2)
Decisive coefficient (R2), root mean square error (RMSE), mean absolute error (MAE), and the relative mean bias (RMB) indicators are used to evaluate the performance of the estimates
Summary
An aerosol is a general term for the solid or liquid particles suspended in the atmosphere with a diameter of 10−3–102 μm [1,2]. The primary methods of AOD acquisition are ground measurements, which do not exhibit spatial continuity and cannot meet the needs of regional research because ground measurements are restricted by the distribution of observation stations. Based on its unique advantages, remote sensing (RS) is an AOD acquisition method that is feasible over a wide range of spatial scales and has a high temporal resolution, which can greatly make up for the shortage of ground-based observation data and solve problems related to the lack of data and uneven spatial distribution. RS provides a reference for comprehensively understanding the concentration and distribution of AOD and offers theoretical support for regional atmospheric environment management
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