Nonstationary Analysis of Aerosol Extinction Coefficient in Chengdu During Autumn and Winter

Meng Yang; Changjian Ni; Zisheng Meng; Xinyi Li

doi:10.3788/LOP202158.1901002

Laser & Optoelectronics Progress, Volume. 58, Issue 19, 1901002(2021)

Nonstationary Analysis of Aerosol Extinction Coefficient in Chengdu During Autumn and Winter

Meng Yang¹, Changjian Ni^1、*, Zisheng Meng¹, and Xinyi Li²

¹Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, College of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu , Sichuan 610225, China

²Chengdu Meteorological Service, Chengdu , Sichuan 611130, China

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Figures & Tables(14)

Fig. 2. Centile curves plots based on M0 and M1b_5 models. (a) M0; (b) M1b_5

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Fig. 3. AIC value of aerosol extinction coefficient sequence model

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Fig. 4. Centile curves plots based M2b model

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Fig. 6. Contribution of each variable in the critical period and the aerosol extinction coefficient

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Table 1. External covariates
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Table 1. External covariates
External covariate Variable Unit
Mass concentration PM_2.5 μg /m³
Relative humidity RH %
Aerosol component structure $ρ_{P M_{2.5}} / ρ_{P M_{10}}$ %

Table 2. Parameters of the candidate models

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Table 2. Parameters of the candidate models

Model code	Variable	Description
M0	-	stationary model
M1a	T	linear time model
M1b	T	nonlinear time model
M2a	external covariates	single covariate
M2b	external covariates	multiple covariates，identified by the stepwise selection

Table 3. Statistical parameters of aerosol extinction coefficient time series
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Table 3. Statistical parameters of aerosol extinction coefficient time series
Time Mean /km^-1 Standard deviation Skewness coefficient Kurtosis coefficient Variation coefficient
2015 0.67 0.53 2.28 9.11 0.79
2016 1.08 0.74 1.41 2.96 0.68
2017 0.71 0.51 1.69 4.01 0.72

Table 4. AIC values of M0 and M1 models

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Table 4. AIC values of M0 and M1 models

Model code	θ₁	θ₂	2015	2016	2017
M0	ct	ct	785.6	1880.7	704.7
M1a_1	T	ct	722.1	1879.7	695.4
M1a_2	ct	T	779.5	1879.5	697.3
M1a_3	T	T	724.0	1877.5	686.0
M1b_1	X_cs（T）	ct	500.8	1597.3	533.2
M1b_2	X_cs（T）	T	499.1	1783.0	535.0
M1b_3	ct	X_cs（T）	703.1	1783.1	670.8
M1b_4	T	X_cs（T）	643.2	1765.3	646.3
M1b_5	X_cs（T）	X_cs（T）	462.8	1535.9	520.6

Table 5. Aerosol extinction coefficient sequence based on M2 model
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Table 5. Aerosol extinction coefficient sequence based on M2 model
Time θ₁ θ₂ AIC
2015 PM_2.5+RH+PM_2.5/PM₁₀ PM_2.5 -437.6
2016 PM_2.5+RH+PM_2.5/PM₁₀ PM_2.5+RH 264.2
2017 PM_2.5+RH+PM_2.5/PM₁₀ PM_2.5+RH+PM_2.5/PM₁₀ -165.1

Table 6. Residual analysis results based on the M2b model
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Table 6. Residual analysis results based on the M2b model
Time Mean Variance Skewness Kurtosis PPCC
2015 -0.012 1.001 -0.131 3.291 0.998
2016 -0.011 1.001 -0.426 3.346 0.992
2017 -0.010 1.001 -0.018 3.477 0.998

Table 7. Average contribution of each variable to the nonstationarity of aerosol extinction coefficient series
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Table 7. Average contribution of each variable to the nonstationarity of aerosol extinction coefficient series
Parameter PM_2.5 RH PM_2.5/PM₁₀
2015 0.308 0.247 0.101
2016 0.333 0.264 0.043
2017 0.390 0.230 0.033

Table 8. Key period of explosive growth of aerosol extinction coefficient

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Table 8. Key period of explosive growth of aerosol extinction coefficient

Process code	Time	Aerosol extinction coefficient /km^-1
Process code	Time	Min	Max
Process 1	20151103T1400—20151104T0100	0.548	1.803
Process 2	20161205T1400—20161205T2300	0.238	3.463
Process 3	20171218T1400—20171219T0000	0.332	2.281

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Meng Yang, Changjian Ni, Zisheng Meng, Xinyi Li. Nonstationary Analysis of Aerosol Extinction Coefficient in Chengdu During Autumn and Winter[J]. Laser & Optoelectronics Progress, 2021, 58(19): 1901002

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