A Study on the Characteristic Variations of Fine Particle in Busan and Ulsan through Particle Extinction Efficiency Analysis

Joo, Sohee; Dehkhoda, Naghmeh; Noh, Youngmin

doi:10.5572/kosae.2021.37.1.080

Cited by 4 publications

(4 citation statements)

References 18 publications

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“…The average α e f f 2.5 was higher than the measured values in previous other studies (Table 1) primarily conducted in China. One study measured the α e f f 2.5 in Busan, Korea, as 4.1-12.1 m 2 g −1 [46]. We attributed these differences to the influence of relative humidity.…”

Section: Mass Extinction Efficiencymentioning

confidence: 87%

“…Second, we did not consider the effects of relative humidity. Many studies confirmed that relative humidity has a high impact on visibility [30,35,36,[42][43][44][45][46]. The correlation coefficient of the mass concentration of PM 2.5 and visibility data increased from 0.81 to 0.89 when correcting for the relative humidity [47].…”

Section: Extinction Coefficientmentioning

confidence: 95%

“…Liu et al [45] confirmed that the MEE in Nanjing, China, increased from 7.1 m 2 g −1 in 2013 to 9.3 m 2 g −1 in 2018. Joo et al [46] also stated that the MEE of PM 2.5 increased by 0.72 m 2 g −1 annually during 2015-2019.…”

Section: Mass Extinction Efficiencymentioning

confidence: 95%

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Estimation of Aerosol Extinction Coefficient Using Camera Images and Application in Mass Extinction Efficiency Retrieval

2022

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In this study, we attempted to calculate the extinction parameters of PM2.5 using images from a commercial camera. The photo pixels provided information on the characteristics of the objects (i.e., the reflectivity, transmittance, or extinction efficiency) and ambient brightness. Using the RGB values of pixels, we calculated the extinction coefficient and efficiency applied to the mass concentration of PM2.5. The calculated extinction coefficient of PM2.5 determined from the camera images had a higher correlation with the PM2.5 mass concentration (R2 = 0.7) than with the visibility data, despite the limited mass range. Finally, we identified that the method of calculating extinction parameters using the effective wavelength of RGB images could be applied to studies of changes in the atmosphere and aerosol characteristics. The mass extinction efficiency of PM2.5, derived from images, and the mass concentration of PM2.5 was (10.8 ± 6.9) m2 g−1, which was higher than the values obtained in Northeast Asia by previous studies. We also confirmed that the dry extinction efficiency of PM2.5, applied with a DRH of 40%, was reduced to (6.9 ± 5.0) m2 g−1. The extinction efficiencies of PM2.5, calculated in this study, were higher than those reported in previous other studies. We inferred that high extinction efficiency is related to changes in size or the composition of aerosols; therefore, an additional long-term study must be conducted.

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Section: Mass Extinction Efficiencymentioning

confidence: 87%

Section: Extinction Coefficientmentioning

confidence: 95%

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Estimation of Aerosol Extinction Coefficient Using Camera Images and Application in Mass Extinction Efficiency Retrieval

2022

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“…Joo et al, 2021 reported that extinction efficiencies in Korea increased although the PM 2.5 mass concentration decreased. This result suggests that even though the PM 2.5 concentration decreased compared to the past, either particle size of PM 2.5 became smaller or the number of particles with high scattering efficiency increased [77]. Uno et al, 2020 stated that the chemical composition of aerosols in East Asia changed significantly [78].…”

Section: åNgström Exponent and Fmf: Annual Trendsmentioning

confidence: 99%

Long-Term Variation Study of Fine-Mode Particle Size and Regional Characteristics Using AERONET Data

et al. 2022

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To identify the long-term trend of particle size variation, we analyzed aerosol optical depth (AOD, τ) separated as dust (τD) and coarse-(τPC) and fine-pollution particles (τPF) depending on emission sources and size. Ångström exponent values are also identified separately as total and fine-mode particles (αT and αPF). We checked these trends in various ways; (1) first-order linear regression analysis of the annual average values, (2) percent variation using the slope of linear regression method, and (3) a reliability analysis using the Mann–Kendall (MK) test. We selected 17 AERONET sun/sky radiometer sites classified into six regions, i.e., Europe, North Africa, the Middle East, India, Southeast Asia, and Northeast Asia. Although there were regional differences, τ decreased in Europe and Asian regions and increased in the Middle East, India, and North Africa. Values of τPC and τPF, show that aerosol loading caused by non-dust aerosols decreased in Europe and Asia and increased in India. In particular, τPF considerably decreased in Europe and Northeast Asia (95% confidential levels in MK-test), and τPC decreased in Northeast Asia (Z-values for Seoul and Osaka are −2.955 and −2.306, respectively, statistically significant if |z| ≥ 1.96). The decrease in τPC seems to be because of the reduction of primary and anthropogenic emissions from regulation by air quality policies. The meaningful result in this paper is that the particle size became smaller, as seen by values of αT that decreased by −3.30 to −30.47% in Europe, North Africa, and the Middle East because αT provides information on the particle size. Particle size on average became smaller over India and Asian regions considered in our study due to the decrease in coarse particles. In particular, an increase of αPF in most areas shows the probability that the average particle size of fine-mode aerosols became smaller in recent years. We presumed the cause of the increase in αT is because relatively large-sized fine-mode particles were eliminated due to air quality policies.

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Long-term variation study of fine-mode particle size and regional characteristics using AERONET data

Shin

Sim

Dehkhoda

et al. 2022

Preprint

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Abstract. To identify the long-term trend of particle size variation, we analyzed aerosol optical depth (AOD, τ) separated as dust (τD) and coarse-(τPC) and fine-pollution particles (τPF) depending on emission sources and size. Ångström Exponent values are also identified separately as total and fine-mode particles (αT and αPF). We checked these trends in various ways; 1) first-order linear regression analysis of the annual average values, 2) percent variation using the slope of linear regression method, and 3) a reliability analysis using the Mann-Kendall (MK) test. We selected 17 AERONET sun/sky radiometer sites classified into six regions, i.e., Europe, North Africa, the Middle East, India, Southeast Asia, and Northeast Asia. τ decreased in Europe and Asian regions and increased in the Middle East, India, and North Africa. Values of τPC and τPF, show that aerosol loading caused by non-dust aerosols decreased in Europe and Asia and increased in India. In particular, τPF considerably decreased in Europe and Northeast Asia (95 % confidential levels in MK-test), and τPC decreased in Northeast Asia (Z-values for Seoul and Osaka are -2.95 and -2.31, respectively). The change in τPC reflects the reduction of primary emissions from plants and other anthropogenic sources as the result of regulations by air policies. Values of αT decreased by -3.3 to -30.5 % in Europe, North Africa, and the Middle East, which means the mean size of aerosol particles increased. Particle size on average became smaller over India and Asian regions considered in our study. We find that αT increased by 1.3 to 13.1 %. In particular, αPF increased in most areas., showing the probability that the average particle size of fine-mode aerosols became smaller in recent years.

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A Study on the Characteristic Variations of Fine Particle in Busan and Ulsan through Particle Extinction Efficiency Analysis

Cited by 4 publications

References 18 publications

Estimation of Aerosol Extinction Coefficient Using Camera Images and Application in Mass Extinction Efficiency Retrieval

Estimation of Aerosol Extinction Coefficient Using Camera Images and Application in Mass Extinction Efficiency Retrieval

Long-Term Variation Study of Fine-Mode Particle Size and Regional Characteristics Using AERONET Data

Long-term variation study of fine-mode particle size and regional characteristics using AERONET data

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