Impact of Fine Particulate Matter on Visibility at Incheon International Airport, South Korea

Won, Wan-Sik; Oh, Rosy; Lee, Woojoo; Kim, Ki‐Young; Ku, Sung-Kwan; Su, Pei-Chen; Yoon, Yong‐Jin

doi:10.4209/aaqr.2019.03.0106

Cited by 24 publications

(20 citation statements)

References 33 publications

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“…The increase of values of Rh, P, and PM 10 results in the decrease of Vis, while the increase of T results in an increase of Vis. These results are in the agreement with earlier studies (e.g., Deng et al, 2014;Majewski et al, 2015;Aman et al, 2019;Araghi et al, 2019;Won et al, 2020). The concentrations of CO and SO 2 are independent variables only in the model where Vis lim1 = 10 km, and the increase of both of them decreases visibility.…”

Section: The Logistic Regression Modelsupporting

confidence: 93%

Predicting the Number of Days With Visibility in a Specific Range in Warsaw (Poland) Based on Meteorological and Air Quality Data

Majewski

Szeląg

Mach

et al. 2021

Front. Environ. Sci.

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Atmospheric visibility is an important parameter of the environment which is dependent on meteorological and air quality conditions. Forecasting of visibility is a complex task due to the multitude of parameters and nonlinear relations between these parameters. In this study, meteorological, air quality, and atmospheric visibility data were analyzed together to demonstrate the capabilities of the multidimensional logistic regression model for visibility prediction. This approach allowed determining independent variables and their significance to the value of the atmospheric visibility in four ranges (i.e., 0–10, 10–20, 20–30, and ≥ 30 km). We proved that the Iman–Conover (IC) method can be used to simulate a time series of meteorological and air quality parameters. The visibility in Warsaw (Poland) is dependent mainly on air temperature and humidity, precipitation, and ambient concentration of PM10. Three logistic models of visibility allowed us to determine precisely the number of days in a month with visibility in a specific range. The sensitivity of the models was between 75.53 and 90.21%, and the specificity 78.51 and 96.65%. The comparison of the theoretical (modeled) with empirical (measured) distribution with the Kolmogorov–Smirnov test yielded p-values always above 0.27 and, in half of the cases, above 0.52.

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Section: The Logistic Regression Modelsupporting

confidence: 93%

Predicting the Number of Days With Visibility in a Specific Range in Warsaw (Poland) Based on Meteorological and Air Quality Data

Majewski

Szeląg

Mach

et al. 2021

Front. Environ. Sci.

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“…The PM 2.5 affects visibility significantly more than the CPM, but in weather conditions such as dust and haze as well as low RH, the CPM effects are sometimes not negligible. Increasing wind speed is associated with decreasing PM 2.5 concentration and visibility recovery, whereas the CPM exhibits a relationship in which its concentration increases with wind speed 46 . This is also related to the generation and transport mechanisms of the PM 10 , as revealed by previous studies 45 , 60 .…”

Section: Discussionmentioning

confidence: 94%

“…This is explained by the negative correlations in the RH–WS plot (− 0.27), demonstrating that low wind speed and high humidity values are related to high PM 2.5 concentrations. Since these conditions are common under stable atmospheric conditions, several studies have revealed their association with PM 2.5 stagnation 18 , 45 , 46 . In the WX–CPM box plot, the CPM commonly displays high concentrations in dust, while in the WX–PM 2.5 box plot, the highest PM 2.5 concentrations occur in haze and dust.…”

Section: Resultsmentioning

confidence: 99%

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Hygroscopic properties of particulate matter and effects of their interactions with weather on visibility

Won

Lee

et al. 2021

Sci Rep

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The hygroscopic property of particulate matter (PM) influencing light scattering and absorption is vital for determining visibility and accurate sensing of PM using a low-cost sensor. In this study, we examined the hygroscopic properties of coarse PM (CPM) and fine PM (FPM; PM2.5) and the effects of their interactions with weather factors on visibility. A censored regression model was built to investigate the relationships between CPM and PM2.5 concentrations and weather observations. Based on the observed and modeled visibility, we computed the optical hygroscopic growth factor, $$f\left( {RH} \right)$$ f RH , and the hygroscopic mass growth, $$GM_{VIS}$$ G M VIS , which were applied to PM2.5 field measurement using a low-cost PM sensor in two different regions. The results revealed that the CPM and PM2.5 concentrations negatively affect visibility according to the weather type, with substantial modulation of the interaction between the relative humidity (RH) and PM2.5. The modeled $$f\left( {RH} \right)$$ f RH agreed well with the observed $$f\left( {RH} \right)$$ f RH in the RH range of the haze and mist. Finally, the RH-adjusted PM2.5 concentrations based on the visibility-derived hygroscopic mass growth showed the accuracy of the low-cost PM sensor improved. These findings demonstrate that in addition to visibility prediction, relationships between PMs and meteorological variables influence light scattering PM sensing.

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“…Various adverse effects of heavy metals on human, animal, plant, soil and aquatic health also abound ( Ogunkunle et al., 2013 ; Ogunkunle and Fatoba, 2014 ). By absorption and scattering of radiations, particles have been known to affect visibility with attendant effects of flight navigation ( Won et al., 2020 ).…”

Section: Common Anthropogenic Air Pollutants: Sources and Adverse Effmentioning

confidence: 99%

Drivers of anthropogenic air emissions in Nigeria - A review

Okedere

Elehinafe

Oyelami

et al. 2021

Heliyon

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This study presents a review of sources and atmospheric levels of anthropogenic air emissions in Nigeria with a view to reviewing the existence or otherwise of national coordination aimed at mitigating the continued increase. According to individual researcher's reports, the atmospheric loading of anthropogenic air pollutants is currently on an alarming increase in Nigeria. Greater concerns are premised on the inadequacy existing emission inventories, continuous assessment, political will and development of policy plans for effective mitigation of these pollutants. The identified key drivers of these emissions include gas flaring, petroleum product refining, thermal plants for electricity generation, transportation, manufacturing sector, land use changes, proliferation of small and medium enterprises, medical wastes incineration, municipal waste disposal, domestic cooking, bush burning and agricultural activities such as land cultivation and animal rearing. Having identified the key sources of anthropogenic air emissions and established the rise in their atmospheric levels through aggregation of literature reports, this study calls for a review of energy policy, adoption of best practices in the management air emissions and solid wastes as well as agriculture and land use pattern which appear to be the rallying points of all identified sources of emission. The study concluded that the adoption of cleaner energy policies and initiatives in energy generation and usage as against pursuit of thermal plants and heavy dependence on fossil fuels will assist to ameliorate the atmospheric loadings of these pollutants.

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Impact of Fine Particulate Matter on Visibility at Incheon International Airport, South Korea

Cited by 24 publications

References 33 publications

Predicting the Number of Days With Visibility in a Specific Range in Warsaw (Poland) Based on Meteorological and Air Quality Data

Predicting the Number of Days With Visibility in a Specific Range in Warsaw (Poland) Based on Meteorological and Air Quality Data

Hygroscopic properties of particulate matter and effects of their interactions with weather on visibility

Drivers of anthropogenic air emissions in Nigeria - A review

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