Retrieval of Aerosol Optical Properties by Skyradiometer over Urban Beijing

Yang Xianyi; Che Huizheng; Chen Quanliang; Liang Yuanxin

doi:10.11898/1001-7313.20200311

Vol.31, NO.3, 2020

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Article Navigation > Journal of Applied Meteorological Science > 2020 > 31(3): 373-384

Yang Xianyi, Che Huizheng, Chen Quanliang, et al. Retrieval of aerosol optical properties by skyradiometer over urban Beijing. J Appl Meteor Sci, 2020, 31(3): 373-384. DOI: 10.11898/1001-7313.20200311.

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Retrieval of Aerosol Optical Properties by Skyradiometer over Urban Beijing

DOI: 10.11898/1001-7313.20200311

1.
School of Atmospheric Sciences, Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, Chengdu University of Information Technology, Chengdu 610225
2.
State Key Laboratory of Severe Weather (LASW), CMA Key Laboratory for Atmospheric Chemistry, Chinese Academy of Meteorological Sciences, Beijing 100081

Received Date: 2020-01-13
Rev Recd Date: 2020-03-15
Publish Date: 2020-05-31

Abstract

Abstract

Aerosol particles can scatter and absorb solar radiation and affect microphysical processes of clouds to change the earth's radiation budget. It is reported that aerosol particles not only have an impact on climate change, but also cause polluted environment and affect human health. Ground-based measurement networks such as AERONET and SKYNET are very useful and accurate ways to monitor the spatio-temporal distribution of aerosols using the sun-sky radiometric technique. Aerosol optical properties retrieved by a PREDE skyradiometer are used to analyze the variation of aerosol in Beijing from October 2018 to September 2019. Results show that aerosol optical depth at 500 nm is high from February to July, the highest value is 0.71 in June, the highest single scattering albedo is 0.96 in August and the lowest value is 0.89 in May, Ångström exponent in summer (1.11) is higher than that in spring (0.89), and the volume size distribution pattern shows typical bimodal in every month. According to the Chinese National Secondary Standards for PM_2.5, pollution days are picked. It is found that pollution days only account for 17%, of which 62% are light pollution days. The statistical result of air quality in Beijing is good from October 2018 to September 2019. Aerosol optical properties and PM_2.5 under pollution and clean weather conditions in Beijing are discussed. The value of PM_2.5 under pollution weather condition is 2.27 times larger than that under clean weather condition, values of aerosol optical depth at 500 nm are 0.85 and 0.49 under pollution and clean weather conditions, respectively. Values of single scattering albedo are 0.96 and 0.92 under pollution and clean weather conditions, respectively. The value of Ångström exponent under pollution weather condition (1.02) is larger than that under clean weather condition (0.91) in winter while the value of Ångström exponent under pollution weather condition (0.87) is smaller than that under clean weather condition (0.90) in spring. Skyradiometer retrieved data, combined with lidar measurement and meteorological data are used to analyze a serious pollution event in winter over Beijing. The result suggests that poor meteorological conditions (low wind speed and high relative humidity), the hygroscopic growth of aerosol, aerosol secondary transformation, local emissions and regional transportation lead to this serious pollution event.
- skyradiometer;
- aerosol optical properties;
- pollution weather condition;
- Beijing

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References(35)

Figures and Tables

图 1 北京城区(39.933°N, 116.317°E, 105 m)天空辐射计观测气溶胶光学厚度与MODIS卫星反演气溶胶光学厚度对比

(实线和虚线分别表示1:1线和期望误差分界线)

Fig. 1 Comparison of the aerosol optical depth observed by skyradiometer and those of MODIS in Beijing(39.933°N, 116.317°E, 105 m)

(solid and dashed lines denote one-one line and the expected error line, respectively)

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图 2 2018年10月—2019年9月北京城区气溶胶光学特性的逐月变化

(a)500 nm气溶胶光学厚度，(b)500 nm单次散射反照率，(c)440~870 nm Ångström波长指数

Fig. 2 Monthly averaged variation in aerosol optical properties from skyradiometer measurements in Beijing from Oct 2018 to Sep 2019

(a)aerosol optical depth at 500 nm, (b)single scattering albedo at 500 nm, (c)Ångströmm exponent at 440-870 nm

DownLoad: Full-Size Img PowerPoint

Fig. 3 Monthly averaged variation in volume size distribution from skyradiometer measurements in Beijing from Oct 2018 to Sep 2019

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图 4 2018年10月—2019年9月北京城区不同气溶胶类型的粒子谱分布

(a)强吸收性粒子，(b)中度吸收性粒子，(c)弱吸收性粒子

Fig. 4 Volume size distribution of different aerosol types in Beijing from Oct 2018 to Sep 2019

(a)highly absorbing particles, (b)moderately absorbing particles, (c)weakly absorbing particles

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图 5 2019年1月北京城区500 nm气溶胶光学厚度和PM_2.5浓度日平均值变化

(阴影部分代表污染事件)

Fig. 5 Daily averaged aerosol optical depth at 500 nm and PM_2.5 in Beijing from 1 Jan to 31 Jan in 2019

(the shaded denotes pollution period)

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图 6 2019年1月8—15日颗粒物浓度和气象要素变化

(a)PM_2.5与PM₁₀浓度变化, (b)能见度与相对湿度变化

Fig. 6 Temporal variation of particulate concentration and meteorological elements from 8 Jan to 15 Jan in 2019

(a)PM_2.5 and PM₁₀, (b)visibility and relative humidity

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Fig. 7 Daily averaged variation of Ångström exponent from skyradiometer in Beijing from 8 Jan to 15 Jan in 2019

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Fig. 8 Averaged volume size from skyradiometer in Beijing from 8 Jan to 15 Jan in 2019

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Fig. 9 Temporal and spatial distribution of extinction coefficient(a) and the depolarization ratio(b) at 532 nm in Beijing from 9 Jan to 14 Jan in 2019

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Table 1 Air quality rank statistics from 11 Oct 2018 to 30 Sep 2019

PM_2.5浓度/(μg·m^-3)	空气质量等级	实际日数/d	仪器有效观测日数/d
(0, 35]	优	171	135
(35, 75]	良	123	103
(75, 115]	轻度污染	38	24
(115, 150]	中度污染	12	8
(150, 250]	重度污染	11	2
(250, 500]	严重污染	0	0

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Table 2 Statistics of aerosol optical depth from 8 Jan to 15 Jan in 2019

日期	波段
日期	400 nm	500 nm	670 nm	870 nm	1020 nm
01-08	0.12	0.10	0.07	0.06	0.05
01-09	0.85	0.68	0.55	0.45	0.40
01-10	0.58	0.42	0.31	0.24	0.21
01-11	1.13	0.89	0.70	0.57	0.51
01-12	0.95	0.71	0.50	0.38	0.33
01-13
01-14	0.77	0.59	0.44	0.35	0.30
01-15	0.16	0.15	0.13	0.12	0.11

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Table 3 Statistics of single scattering albedo from 8 Jan to 15 Jan in 2019

日期	波段
日期	400 nm	500 nm	670 nm	870 nm	1020 nm
01-08	0.90	0.93	0.87	0.82	0.80
01-09	0.93	0.96	0.96	0.97	0.95
01-10	0.94	0.99	0.99	0.97	0.91
01-11	0.92	0.98	0.96	0.95	0.92
01-12	0.93	0.99	0.99	0.97	0.92
01-13
01-14	0.91	0.99	0.99	0.99	0.94
01-15	0.83	0.84	0.82	0.84	0.84

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