Current Challenges in Visibility Improvement in Sichuan Basin

Abstract

Atmospheric visibility (VIS), reflecting the atmosphere transmittance, is an important indicator of air quality (Bäumer et al., 2008). Low visibilities exert significant influences on transportation, especially air traffic (Sun et al., 2021), and thus decrease society efficiencies. China has suffered from air pollution with the rapid economic growth over the past years and the visibility deterioration in China has raised public awareness (Guo et al., 2014). The Chinese government has made many efforts to improve haziness including various strategies of emission control since the issuing of the Air Pollution Prevention Control and Action Plan in 2013. PM 2.5 , NO x , and SO 2 were observed to reduce by 33%, 21%, and 59%, respectively (Zheng et al., 2018). However, the low visibility events occur frequently despite the PM 2.5 mitigation (Xu et al., 2020). The deep blue day, which requires the visibility to be larger than 21.52 km, even decreased in China from 1980 to 2018 (S Wang et al., 2022), which indicates that the visibility repairment lags behind the reduction of PM 2.5 . PM 2.5 was brought down by 30% while the low visibility frequency in the Pearl River Delta regions decreased by only 5% (Xu et al., 2020). The increased aerosol extinction efficiency hinders visibility improvement in Eastern China despite that the PM 2.5 level was reduced by 50.8 μg/m 3 (Yao et al., 2021). More efforts should be devoted to visibility repairment along with the reduction of PM 2.5 .By definition, visibility is the distance at which an observer can barely recognize a black object, and the basic formula of atmospheric visibility is VIR = Inε/σ where ε is a contrast threshold of the observer, and σ is the

Variations of Wintertime Ambient Volatile Organic Compounds in Beijing, China, from 2015 to 2019

“…Satellite-based and ground-based measurements have also corroborated these improvements. 5,6 Significantly decreased trends of sulfur dioxide (SO 2 ), nitrogen dioxide (NO 2 ), fine particulate matter (PM 2.5 ), and carbon monoxide (CO) were found by many studies based on the monitoring network provided by the Chinese government. 7−9 In contrast, a significantly increased trend of 8 h average O 3 is observed.…”

Estimation of fine particulate matter in an arid area from visibility based on machine learning

“…The relationship between visibility and PM 2.5 concentrations may be non-linear and can be affected by many physical factors, such as relative humidity 21 . However, most previous studies have used linear statistic models, such as generalized linear model or linear mixed effects model, to quantify the visibility-PM 2.5 relationship 18 , 19 , 22 .…”