Comparison of PM2.5 in Seoul, Korea Estimated from the Various Ground-Based and Satellite AOD

Kim, Sang-Min; Koo, Ja Ho; Lee, Hana; Mok, Jungbin; Choi, Myungje; Go, Sujung; Lee, Seo-Young; Cho, Yeseul; Hong, Jaemin; Seo, Sora; Lee, Junhong; Hong, Jinkyu; Kim, Jhoon

doi:10.3390/app112210755

Cited by 13 publications

(6 citation statements)

References 48 publications

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“…In winter, the correlation coefficients between AOD and PM 2.5 and AQI were the lowest, at 0.46 and 0.48, respectively. This result is consistent with the findings of many existing studies [34,60]. It also means that the correlation between AOD and AQI was higher than that of PM 2.5 in autumn and winter.…”

Section: Relationship Between Aod and Pm 25 /Aqisupporting

confidence: 93%

“…Many studies have shown that there is a correlation between AOD and PM 2.5 concentrations [30][31][32][33], and many scholars have estimated near-ground atmospheric particulate matter concentrations based on satellite remote sensing AOD products [34][35][36][37][38]. However, the correlation between AOD and PM 2.5 concentrations on a time scale with periodic characteristics is ignored.…”

Section: Introductionmentioning

confidence: 99%

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Spatial and Temporal Variation of Aerosol Optical Depth in Huaihai Economic Zone from 1982 to 2021

Xue

Sun

et al. 2023

Atmosphere

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Aerosol Optical Depth (AOD), quantifying the amount of aerosol in the atmosphere, is widely regarded as a crucial indicator for research on atmospheric physics and regional air quality. At present, the inversion of AOD from observation of satellite remote sensing sensors has become the main technology for large-scale monitoring of aerosol load. The Huaihai Economic Zone is the connecting belt of two key areas of atmospheric governance (the Yangtze River Delta and the Beijing-Tianjin-Hebei region, China), and it has been suffering from air pollution for many years and few studies of AOD focus on this region. Therefore, the spatial and temporal characteristics of the AOD are explored using MODIS AOD data and AVHRR AOD data in this region during the period from 1982 to 2021 in this study. The correlation coefficients between the AOD of satellite observation and actual air pollution were analyzed by combining PM2.5 pollutant concentration and air quality index (AQI) data. The results showed that the AOD is higher in the northwest than in the southeast, and it is different from season to season. The annual variation of AOD in the Huaihai Economic Zone is a W-shaped trend from 1982 to 2011, while the trend of annual AOD is decreasing after 2011. In terms of seasons, the whole differences in AOD are evident, exhibiting AOD values in summer > those in spring > those in autumn > and those in winter. Furthermore, it indicated that the quarterly and monthly variation of the AOD tends to be flat in recent years. Since 2015, the concentration of PM2.5 has continued to decline, the same as that of AQI. Meanwhile, the quarterly and monthly differences in PM2.5 are still obvious, with higher PM2.5 in winter and lower PM2.5 in summer. However, it also represented that PM2.5 is significantly higher in spring than in autumn from 2015 to 2018, which is the opposite for 2019 to 2021. Lastly, the correlation between AOD and PM2.5/AQI is also given; i.e., the correlation coefficients of AOD with PM2.5/AQI are 0.84/0.82, with the highest correlation coefficient in autumn (R = 0.86/0.91) and the lowest in winter (R = 0.46/0.48).

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Section: Relationship Between Aod and Pm 25 /Aqisupporting

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Spatial and Temporal Variation of Aerosol Optical Depth in Huaihai Economic Zone from 1982 to 2021

Xue

Sun

et al. 2023

Atmosphere

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“…Because of error terms or extreme values from observation, local statistics can show bad performance. As indicated in Koo [47], the impact of hygroscopic growth factors on AOD can differ among observational locations. Further studies are required to address this issue.…”

Section: Springtimementioning

confidence: 99%

Validating Aerosol Optical Depth Estimation Methods Using the National Institute of Environmental Research Operational Numerical Forecast Model

et al. 2022

Self Cite

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Currently, significant efforts are being made to enhance the performance of the National Institute of Environmental Research (NIER) operational model. However, the model performance concerning Aerosol Optical Depth (AOD) estimation remains uninvestigated. In this study, three different estimation methods for AOD were implemented using the NIER operational model and validated with satellite and ground observations. In the widely used Interagency Monitoring of Protected Visual Environments (IMPROVE) method, AOD exponentially increases with relative humidity owing to a hygroscopic growth factor. However, alternative methods show better performance, since AOD estimation considers the size dependency of aerosol particles and is not sensitive to high relative humidity, which reduces the high AOD in areas with large cloud fractions. Although some R values are significantly low, especially for a single observational comparison and small numerical domain analysis, one of the alternative estimation methods achieves the best performance for diagnosing AOD in the East Asia region.

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“…The exceedance of pollutants, such as particulate matter, nitrogen dioxide, and ozone, is a major challenge in terms of improving urban air quality [16][17][18][19]. Internationally, the development of AOD inversion algorithms [20][21][22][23][24], the spatiotemporal distribution of AOD and pollution characteristics [25][26][27][28][29][30], PM 2.5 estimation, and others [31][32][33][34][35][36] have been extensively investigated. Most importantly, a thorough understanding of the spatiotemporal distribution patterns of aerosols in various regions, over long time series, and the mechanism of their effects on air pollution and climate change is essential.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Variations of Aerosol Optical Depth and the Spatial Heterogeneity Relationship of Potential Factors Based on the Multi-Scale Geographically Weighted Regression Model in Chinese National-Level Urban Agglomerations

Yuan,

Wang,

Feng

et al. 2023

Remote Sensing

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Investigating the spatiotemporal variation characteristics of aerosol optical depth (AOD) and its driving factors is essential for assessing atmospheric environmental quality and alleviating air pollution. Based on a 22-year high-resolution AOD dataset, the spatiotemporal variations of AOD in mainland China and ten national urban agglomerations were explored based on the Mann–Kendall trend test and Theil–Sen median method. Random forest (RF) and multiscale geographically weighted regression (MGWR) were combined to identify the main driving factors of AOD in urban agglomerations and to reveal the spatial heterogeneity of influencing factors. The results showed that areas with high annual average AOD concentrations were mainly concentrated in the Chengdu–Chongqing, Central Plains, Shandong Peninsula, and Middle Yangtze River urban agglomerations. Southern Beijing–Tianjin–Hebei and its surrounding areas revealed the highest AOD pollution during summer, whereas the worst pollution during the remaining three seasons occurred in the Chengdu–Chongqing urban agglomeration. Temporally, except for the Ha-Chang and Mid-Southern Liaoning urban agglomerations, where the average annual AOD increased, the other urban agglomerations showed a decreasing trend. Among them, the Central Plains, Middle Yangtze River, Guanzhong Plain, and Yangtze River Delta urban agglomerations all exhibited a decline greater than 20%. According to the spatial trends, most urban agglomerations encompassed much larger areas of decreasing AOD values than areas of increasing AOD values, indicating that the air quality in most areas has recently improved. RF analysis revealed that PM2.5 was the dominant factor in most urban clusters, followed by meteorological factors. MGWR results show that the influencing factors have different spatial scale effects on AOD in urban agglomerations. The socioeconomic factors and PM2.5 showed strong spatial non-stationarity with regard to the spatial distribution of AOD. This study can provide a comprehensive understanding of AOD differences among urban agglomerations, and it has important theoretical and practical implications for improving the ecological environment and promoting sustainable development.

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Comparison of PM2.5 in Seoul, Korea Estimated from the Various Ground-Based and Satellite AOD

Cited by 13 publications

References 48 publications

Spatial and Temporal Variation of Aerosol Optical Depth in Huaihai Economic Zone from 1982 to 2021

Spatial and Temporal Variation of Aerosol Optical Depth in Huaihai Economic Zone from 1982 to 2021

Validating Aerosol Optical Depth Estimation Methods Using the National Institute of Environmental Research Operational Numerical Forecast Model

Spatiotemporal Variations of Aerosol Optical Depth and the Spatial Heterogeneity Relationship of Potential Factors Based on the Multi-Scale Geographically Weighted Regression Model in Chinese National-Level Urban Agglomerations

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