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Table 1.

Summary of the abbreviations and acronyms used in this study.

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Table 1 Expand

Figure 1.

Thirty-eight year trend of monthly average visual range measurements from January 1973 to December 2010 and air pollution index from June 2000 to December 2010 in Chengdu, China.

The red solid lines indicate the long-term trends determined by a regression model based on the least squares method.

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Figure 1 Expand

Table 2.

Coefficients of the regression model for visual range (VR) and air pollution index (API) during Period-1 (1973–1982), Period-2 (1983–1995), Period-3 (1996–2005), and Period-4 (2006–2010) in Chengdu.

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Figure 2.

Scatter plot of visual range versus industrial emissions including industrial dust, soot, and sulfur dioxide during 2005–2010.

The dash lines represent the linear trend determined by regression. The color bar shows the year for the industrial emissions.

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Figure 2 Expand

Figure 3.

Annual variations of ridit values during 1973–2010 in Chengdu.

Ridit values >0.5 mean that the visual range for the year was better than the reference distribution established from the 1973–2010 data; the opposite is true for value <0.5. Solid lines are linear fits of the ridit trends.

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Figure 4.

Left panel: Spatial and seasonal distributions of average MODIS/Aqua AOD at 550 nm.

Right panel: light extinction coefficient (bext) estimated from Koschmieder’s formula over the Sichuan Basin during March 2009 to February 2010.

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Figure 5.

Scatter plots of ammonium calculated from (a) 0.29×[NO3] +0.19×[SO42] and (b) 0.29×[NO3] +0.38×[SO42] versus ammonium measured by ion chromatography.

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Figure 6.

Daily variations of the contributions of PM2.5 chemical components and aerosol moisture to the light extinction coefficient (bext) for the intensive sampling period based on the revised IMPROVE equation.

The aerosol moisture contributions were calculated from bext under ambient condition subtracts bext under dry condition.

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Table 3.

Average chemical component concentrations and meteorological parameters for the best and worst visual ranges (VRs).

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Table 3 Expand

Table 4.

Changes in light extinction (bext) budgets for PM2.5 components and moisture for the Best 2.5% and the Worst 2.5% visual range observations.

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Figure 7.

Correlations between AOD at 550 nm and light extinction by PM2.5 NH4HSO4, NH4NO3, moisture, organic matter (OM), elemental carbon (EC), and soil dust.

The color bars indicate the concentrations of the chemical species or relative humidity (RH).

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Figure 8.

Average source contribution (in percent) for each PMF source factor to PM2.5 mass concentration and dry particle light scattering coefficient (bsp,dry).

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