Comparative influences of airborne pollutants and meteorological parameters on atmospheric visibility and turbidity

Wen, Chi‐Chung; Yeh, Hui-Hsuan

doi:10.1016/j.atmosres.2009.12.005

Cited by 38 publications

(23 citation statements)

References 27 publications

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“…An exponential correlation has been found between visibility and aerosol mass concentration (Wen et al, 2010). It has also been reported that the mixing state of black carbon (BC, i.e.…”

Section: Introductionmentioning

confidence: 85%

“…Studies regarding the trends of visibility (Deng et al, 2008;Chang et al, 2009), source apportionment of visibility impairment (Ying et al, 2004) and the correlation between visibility and its influencing factors have shown that visibility was largely influenced by the particle size distribution (Motallebi, et al, 1990;Cheng et al, 2008b), meteorological conditions (Wu et al, 2005;Deng et al, 2008;Zhang et al, 2010) and aerosol chemical components (Randles, et al, 2004;Armin Sorooshian, et al, 2008;Wen et al, 2010). An exponential correlation has been found between visibility and aerosol mass concentration (Wen et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

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A parameterization of low visibilities for hazy days in the North China Plain

et al. 2012

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Abstract. Visibility degradation is a pervasive and urgent environmental problem in China. The occurrence of low visibility events is frequent in the North China Plain, where the aerosol loading is quite high and aerosols are strongly hygroscopic. A parameterization of light extinction (K ex ) for low visibilities on hazy days is proposed in this paper, based on visibility, relative humidity (RH), aerosol hygroscopic growth factors and particle number size distributions measured during the Haze in China (HaChi) Project. Observational results show that a high aerosol volume concentration is responsible for low visibility at RH <90 %; while for RH >90 %, decrease of visibility is mainly influenced by the increase of RH. The parameterization of K ex is developed on the basis of aerosol volume concentrations and RH, taking into accounts the sensitivity of visibility to the two factors and the availability of corresponding data. The extinction coefficients calculated with the parameterization schemes agree well with the directly measured values.

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“…An exponential correlation has been found between visibility and aerosol mass concentration (Wen et al, 2010). It has also been reported that the mixing state of black carbon (BC, i.e.…”

Section: Introductionmentioning

confidence: 85%

Section: Introductionmentioning

confidence: 99%

A parameterization of low visibilities for hazy days in the North China Plain

et al. 2012

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“…The particle number size distribution and chemical composition and relative refractive index 4148 Z. Zhang et al: Analysis of extinction properties using a κ-EC-Mie model in Nanjing are the important parameters that affect the optical properties of the particles (Day et al, 2000;Ma et al, 2012;Cheng et al, 2008a;Wen and Yeh, 2010). However, many of the aerosol components are hygroscopic and take up water as a function of the relative humidity (RH) (Clarke et al, 2004;Covert et al, 1972;Swietlicki et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

Analysis of extinction properties as a function of relative humidity using a <i>κ</i>-EC-Mie model in Nanjing

Zhang

Shen²,

et al. 2017

Atmos. Chem. Phys.

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Abstract. The relationship between relative humidity (RH) and extinction properties is of widespread concern. In this study, a hygroscopic parameter (κ) and the volume fraction of elemental carbon (EC) were used to characterize the chemical characteristics of particles, and a core-shell model was built based on these characteristics. The size distribution, chemical composition, and RH were measured in Nanjing from 15 October to 13 November 2013. The modelderived extinction coefficients of particles were fit with the program of coated spheres according to Bohren and Huffman (2008) (BHCOAT), and the modeled values correlated well with the measurement-derived extinction coefficients (r 2 = 0.81), which suggested that the core-shell model produced reasonable results. The results show that more than 81 % of the extinction coefficient in Nanjing was due to particles in the 0.2-1.0 µm size range. Under dry conditions, the higher mass fraction of particles in the 0.2-1.0 µm size range caused the higher extinction coefficient. An increase in RH led to a significant increase in the extinction coefficient, although the increases differed among the different size segments. For λ = 550 nm, the extinction coefficient from the 0.01-0.2, 0.2-0.5, and 1.0-2.0 µm size ranges increased significantly with the increase in RH, whereas the extinction contributions from the 0.5-1.0 and 2.0-10.0 µm size ranges to the extinction coefficient decreased slightly.

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“…There is a strong correlation between the presence of PM2.5 and PM10 (particles with aerodynamic diameters smaller than 10 μm), to the extent that a targeted reduction in PM10 is likely to lead to an increase in the atmospheric visibility [15,16]. In addition to the air pollutants, the meteorological parameters (i.e., wind speed and direction, relative air humidity, air temperature, atmospheric pressure and precipitation) can also directly or indirectly affect atmospheric visibility as they influence the local and regional air quality in urban areas [17][18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

The Impact of Selected Parameters on Visibility: First Results from a Long-Term Campaign in Warsaw, Poland

et al. 2015

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Abstract:The aim of this study was to investigate how atmospheric air pollutants and meteorological conditions affected atmospheric visibility in the largest Polish agglomeration. The correlation analysis, principal component analysis (PCA) and generalized regression models (GRMs) were used to accomplish this objective. The meteorological parameters (temperature, relative humidity, precipitation, wind speed and insolation) and concentrations of the air pollutants (PM10, SO2, NO2, CO and O3) were recorded in [2004][2005][2006][2007][2008][2009][2010][2011][2012][2013]. The data came from the Ursynów-SGGW, MzWarszUrsynów and Okęcie monitoring stations, located in the south of Warsaw (Poland). It was shown that the PM10 concentration was the most important parameter affecting the visibility in Warsaw. The concentration, and indirectly the visibility, was mainly affected by the pollutant emission from the flat/building heating (combustion of various fuels). It changed intensively during the OPEN ACCESSAtmosphere 2015, 6 1155 research period. There were also periods in which this emission type did not have a great influence on the pollutant concentrations (mainly PM10) and visibility. In such seasons, the research revealed the influence of the traffic emission and secondary aerosol formation processes on the visibility.

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Comparative influences of airborne pollutants and meteorological parameters on atmospheric visibility and turbidity

Cited by 38 publications

References 27 publications

A parameterization of low visibilities for hazy days in the North China Plain

A parameterization of low visibilities for hazy days in the North China Plain

Analysis of extinction properties as a function of relative humidity using a <i>κ</i>-EC-Mie model in Nanjing

The Impact of Selected Parameters on Visibility: First Results from a Long-Term Campaign in Warsaw, Poland

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Comparative influences of airborne pollutants and meteorological parameters on atmospheric visibility and turbidity

Cited by 38 publications

References 27 publications

A parameterization of low visibilities for hazy days in the North China Plain

A parameterization of low visibilities for hazy days in the North China Plain

Analysis of extinction properties as a function of relative humidity using a &lt;i&gt;κ&lt;/i&gt;-EC-Mie model in Nanjing

The Impact of Selected Parameters on Visibility: First Results from a Long-Term Campaign in Warsaw, Poland

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Analysis of extinction properties as a function of relative humidity using a <i>κ</i>-EC-Mie model in Nanjing