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Retrieval of Aerosol Optical Properties by Skyradiometer over Urban Beijing
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摘要: 利用2018年10月—2019年9月天空辐射计观测数据反演北京城区气溶胶光学特性参数，重点分析污染过程中气溶胶光学特性与气象条件的相关性。结果表明：500 nm气溶胶光学厚度在2—7月较大，最高值出现在6月，为0.71。单次散射反照率最高值出现在8月，为0.96；最低值出现在5月，为0.89。440~870 nm Ångström波长指数最高值出现在夏季，为1.11；最低值出现在春季，为0.89。统计发现污染日数仅占总日数的17%，其中62%为轻度污染；污染和清洁天气条件下PM2.5浓度分别为107.22 μg·m-3和47.16 μg·m-3，500 nm气溶胶光学厚度分别为0.85和0.49，单次散射反照率分别为0.96和0.92；冬季Ångström波长指数在污染天气条件下（1.02）大于清洁天气（0.91），春季相反。结合天空辐射计、激光雷达和气象数据分析2019年1月一次污染事件，可知低风速与高湿度等不利气象条件、气溶胶粒子的吸湿增长和二次转化、污染物局地排放及区域输送共同导致污染事件发生。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 PM2.5, 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 PM2.5 under pollution and clean weather conditions in Beijing are discussed. The value of PM2.5 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.
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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)
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
图 3 2018年10月—2019年9月北京城区粒子谱分布逐月变化
Fig. 3 Monthly averaged variation in volume size distribution from skyradiometer measurements in Beijing from Oct 2018 to Sep 2019
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
图 5 2019年1月北京城区500 nm气溶胶光学厚度和PM2.5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 PM2.5 in Beijing from 1 Jan to 31 Jan in 2019
(the shaded denotes pollution period)
图 6 2019年1月8—15日颗粒物浓度和气象要素变化
(a)PM2.5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)PM2.5 and PM10, (b)visibility and relative humidity
图 7 2019年1月8—15日北京城区Ångström波长指数逐日变化
Fig. 7 Daily averaged variation of Ångström exponent from skyradiometer in Beijing from 8 Jan to 15 Jan in 2019
图 8 2019年1月8—15日北京城区粒子谱分布变化
Fig. 8 Averaged volume size from skyradiometer in Beijing from 8 Jan to 15 Jan in 2019
图 9 2019年1月9—14日北京城区532 nm气溶胶消光系数(a)和退偏振比(b)分布
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
表 1 2018年10月11日—2019年9月30日空气质量等级统计
Table 1 Air quality rank statistics from 11 Oct 2018 to 30 Sep 2019
PM2.5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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表 2 2019年1月8—15日气溶胶光学厚度统计
Table 2 Statistics of aerosol optical depth from 8 Jan to 15 Jan in 2019
日期 波段 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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表 3 2019年1月8—15日单次散射反照率统计
Table 3 Statistics of single scattering albedo from 8 Jan to 15 Jan in 2019
日期 波段 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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