Aerosol Optical Properties and Radiative Effects During a Pollution Episode in Beijing

Liang Yuanxin; Che Huizheng; Wang Hong; Peng Yue; Zhang Yangmei; Tao Fa

doi:10.11898/1001-7313.20200506

Vol.31, NO.5, 2020

Turn off MathJax

Article Contents

Article Navigation > Journal of Applied Meteorological Science > 2020 > 31(5): 583-594

Liang Yuanxin, Che Huizheng, Wang Hong, et al. Aerosol optical properties and radiative effects during a pollution episode in Beijing. J Appl Meteor Sci, 2020, 31(5): 583-594. DOI: 10.11898/1001-7313.20200506.

Citation:

Liang Yuanxin, Che Huizheng, Wang Hong, et al. Aerosol optical properties and radiative effects during a pollution episode in Beijing. J Appl Meteor Sci, 2020, 31(5): 583-594. DOI: 10.11898/1001-7313.20200506.

Citation:

PDF( 2912 KB)

Aerosol Optical Properties and Radiative Effects During a Pollution Episode in Beijing

DOI: 10.11898/1001-7313.20200506

1.
State Key Laboratory of Severe Weather (LASW) & CMA Key Laboratory for Atmospheric Chemistry, Chinese Academy of Meteorological Sciences, Beijing 100081
2.
CMA Meteorological Observation Center, Beijing 100081

Received Date: 2020-03-04
Rev Recd Date: 2020-05-28
Publish Date: 2020-09-30

Abstract

Abstract

Based on continuous observations of aerosol optical properties from sun-photometer and PM_2.5 concentration, the variation of aerosol optical depth, single scattering albedo and asymmetry factor during a pollution episode in Beijing from 25 January to 28 January in 2018 are analyzed. Combined with Raman-Mie Lidar vertical detection, the vertical variation of aerosol extinction coefficient is analyzed in detail. Based on ground-based observations, using a shortwave radiative transfer model, the shortwave radiative heating rates under the clear sky background during the pollution episode are calculated. Results show that under clean condition (25 January 2018), the average daily PM_2.5 concentration is 19.00 μg·m^-3, aerosol optical depth at 440 nm is 0.13, single scattering albedo is 0.87, and the extinction coefficient of aerosol is less than 0.10 km^-1. During the pollution episode (26-27 January 2018), the average daily PM_2.5 concentration is 83.21 μg·m^-3, aerosol optical depth is 2.48, single scattering albedo increases to 0.94, the main aerosol extinction layer height increases to 3.00 km and the mean extinction coefficient of the whole layer is 0.43 km^-1. The aerosol layer can heat the atmosphere evidently, the magnitude of radiative heating rates by aerosol depends on distribution of the aerosol in the vertical direction, and the heating rate under the concentrated heating layer decreases rapidly. Under clean condition, extinction coefficient is less than 0.1 km^-1 which causes the shortwave radiative heating rate of aerosol layer within 10.00 K·day^-1. During the pollution episode, the strong heating effect in the middle and upper aerosol layers (1.50-3.00 km) where the average shortwave radiative heating rate reaches 13.89 K·day^-1, while the lower aerosol layer (within 1.50 km) has a weak heating effect, and the average shortwave radiative heating rate within 1.50 km is only 0.99 K·day^-1. Heating rate accuracy is affected by single scattering albedo, the increased aerosol scattering ability would weaken the heating effect on the atmosphere, and the heating rate in pollution condition is more sensitive to changes of aerosol scattering ability. With the mean extinction coefficient of the whole layer being 0.43 km^-1, the increase of single scattering albedo from 0.87 to 0.94 cause the heating rate of the upper and middle aerosol layers decreases by 3.74 K·day^-1, while the heating rate of the lower aerosol layer increases by 0.81 K·day^-1 on 27 January 2018.
- Lidar;
- aerosol extinction coefficient;
- vertical profile;
- radiative heating rate;
- Beijing

FullText(HTML)

References(40)

Figures and Tables

Fig. 1 Daily averaged variation of aerosol optical depth at 440 nm, 675 nm, 870 nm and 1020 nm in Beijing in Jan 2018

DownLoad: Full-Size Img PowerPoint

图 2 2018年1月北京PM_2.5质量浓度变化趋势

(阴影部分代表污染事件)

Fig. 2 Daily and hourly averaged variation of PM_2.5 concentration in Beijing in Jan 2018

(the shaded denotes the pollution period)

DownLoad: Full-Size Img PowerPoint

Fig. 3 Temporal and spatial distribution of extinction coefficient and depolarization ratio at 532 nm in Beijing from 25 Jan to 28 Jan in 2018

DownLoad: Full-Size Img PowerPoint

Fig. 4 Temporal and spatial distribution of cloud radar reflectivity in Beijing from 25 Jan to 28 Jan in 2018

DownLoad: Full-Size Img PowerPoint

Fig. 5 Daily averaged variation of single scattering albedo and mmetry factor at 440 nm, 675 nm, 870 nm and 1020 nm in Beijing from 25 Jan to 28 Jan in 2018

DownLoad: Full-Size Img PowerPoint

Fig. 6 Hourly variation of monthly averaged shortwave downward radiation and solar elevation angle in Beijing in Jan 2018

DownLoad: Full-Size Img PowerPoint

Fig. 7 Day-time averaged vertical distribution of atmospheric extinction coefficient and solar radiative heating rate(0800 BT to 1700 BT) in Beijing from 25 Jan to 28 Jan in 2018

DownLoad: Full-Size Img PowerPoint

Fig. 8 The vertical distribution of solar radiative heating rate with single scattering albedo in clear day and pollution day

DownLoad: Full-Size Img PowerPoint

Fig. 9 Vertical distribution of day-time extinction coefficient and solar radiative heating rate in Beijing on 27 Jan 2018

DownLoad: Full-Size Img PowerPoint

Table 1 Solar wavelength in the shortwave radiation model

波段	分段波长/μm	应用波长/μm
1	(0.175, 0.225]	0.225
2	(0.225, 0.245]	0.245
3	(0.245, 0.260]	0.260
4	(0.280, 0.295]	0.295
5	(0.295, 0.310]	0.310
6	(0.310, 0.320]	0.320
7	(0.320, 0.400]	0.400
8	(0.400, 0.700]	0.532
9	(0.700, 1.220]	1.220
10	(1.220, 2.270]	2.270
11	(2.270, 10.000]	5.000

DownLoad: Download CSV

Table 2 Fitting functions between AOD and wavelength from 25 Jan to 28 Jan in 2018

日期	拟合公式	相关系数
25	lnτ = -1.72lnλ+9.57	0.95
26	lnτ = -1.64lnλ+9.91	0.99
27	lnτ = -0.77lnλ+5.66	0.98
28	lnτ = -1.75lnλ+9.79	0.96

DownLoad: Download CSV

References

[1]	Tegen I, Lacis A, Fung I.The influence on climate forcing of mineral aerosols from disturbed soils.Nature, 1996, 380:419-422. doi: 10.1038/380419a0
[2]	Quijano A, Sokolik I, Toon O.Radiative heating rates and direct radiative forcing by mineral dust in cloudy atmospheric conditions.J Geophys Res, 2000, 105(D10):12207-12219. doi: 10.1029/2000JD900047
[3]	徐影, 丁一汇, 赵宗慈.近30年人类活动对东亚地区气候变化影响的检测与评估.应用气象学报, 2002, 13(5):513-525. http://qikan.camscma.cn/article/id/20020569
[4]	Allen S, Plattner G, Nauels A, et al.Climate change 2013:The physical science basis.An overview of the working group 1 contribution to the fifth assessment report of the intergovernmental panel on climate change (IPCC).Computational Geometry, 2007, 18(2):95-123. https://ui.adsabs.harvard.edu/abs/2013AGUFMGC51A0949A/abstract
[5]	王海啸, 黄建国, 陈长和.城市气溶胶对短波辐射的影响及其在边界层温度变化中的反映.气象学报, 1993, 51(4):457-464.
[6]	李德平, 程兴宏, 孙治安, 等.北京不同区域气溶胶辐射效应.应用气象学报, 2018, 29(5):99-108. doi: 10.11898/1001-7313.20180509
[7]	Xu J, Li C, Shi H, et al.Analysis on the impact of aerosol optical depth on surface solar radiation in the Shanghai megacity.China.Atmos Chem Phys, 2011, 11:3281-3289. doi: 10.5194/acp-11-3281-2011
[8]	申绍华.对流层气溶胶和云的大气辐射加热特征.大气科学, 1991, 15(6):89-98. http://www.cqvip.com/Main/Detail.aspx?id=458035
[9]	Toon O B, McKay C P, Ackerman T P, et al.Rapid calculation of radiative heating rates and photodissociation rates in inhomogeneous multiple scattering atmospheres.J Geophys Res Atmos, 1989, 94(D13):16287-16301. doi: 10.1029/JD094iD13p16287
[10]	Zhang X, Zhong J, Wang J, et al.The interdecadal worsening of weather conditions affecting aerosol pollution in the Beijing area in relation to climate warming.Atmos Chem Phys:Discussions, 2018, 18(8):5991-5999. doi: 10.5194/acp-18-5991-2018
[11]	Wang H, Peng Y, Zhang X, et al.Contributions to the explosive growth of PM_2.5 mass due to aerosol-radiation feedback and decrease in turbulent diffusion during a red alert heavy haze in Beijing-Tianjin-Hebei, China.Atmos Chem Phy, 2018, 18(23):17717-17733. doi: 10.5194/acp-18-17717-2018
[12]	Che H, Xia X, Zhu J, et al.Column aerosol optical properties and aerosol radiative forcing during a serious haze-fog month over North China Plain in 2013 based on ground-based sunphotometer measurements.Atmos Chem Phy, 2014, 14(4):2125-2138. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=16519196781ee0e1612fcddc03363208
[13]	García O E, Díaz J P, Expósito F J, et al.Aerosol Radiative Forcing: AERONET Based Estimates, Climate Models.2012.
[14]	Li Z, Xia X, Cribb M, et al.Aerosol optical properties and their radiative effects in northern China.J Geophys Res, 2007, 112:D22S01. http://meto.umd.edu/~zli/PDF_papers/Li%20et%20al.%202006JD007382.pdf
[15]	Zheng Y, Che H, Xia X, et al.Five-year observation of aerosol optical properties and its radiative effects to planetary boundary layer during air pollution episodes in North China:Intercomparison of a plain site and a mountainous site in Beijing.Science of The Total Environment, 2019, 674:140-158. doi: 10.1016/j.scitotenv.2019.03.418
[16]	Liou K, Sasamori T.On the transfer of solar radiation in aerosol atmosphere.J Atmos Sci, 1975, 2:2166-2177. http://iopscience.iop.org/1757-899X/65/1/012007
[17]	张华, 马井会, 郑有飞.黑碳气溶胶辐射强迫全球分布的模拟研究.大气科学, 2008, 32(5):1147-1158. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=daqikx200805013
[18]	王宏, 石广玉, 王标, 等.中国沙漠沙尘气溶胶对沙漠源区及北太平洋地区大气辐射加热的影响.大气科学, 2007, 33(1):515-526. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=daqikx200703015
[19]	田华, 马建中, 李维亮, 等.中国中东部地区硫酸盐气溶胶直接辐射强迫及气候效应的数值模拟.应用气象学报, 2005, 16(3):322-333. http://qikan.camscma.cn/article/id/20050341
[20]	迟如利, 吴德成, 刘博, 等.双波长米散射激光雷达探测对流层气溶胶消光特性.光谱学与光谱分析, 2009, 29(6):1468-1472. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=gpxygpfx200906007
[21]	Sheng Z, Che H, Chen Q, et al.Aerosol vertical distribution and optical properties of different pollution events in Beijing in autumn 2017.Atmos Res, 2019, 215:193-207. doi: 10.1016/j.atmosres.2018.08.029
[22]	刘东, 陶宗明, 吴德成, 等.三波长拉曼偏振激光雷达系统研制及探测个例.光学学报, 2013, 33(2):223-228. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=gxxb201302037
[23]	沈吉, 曹念文.米-拉曼散射激光雷达反演对流层气溶胶消光系数廓线.中国激光, 2017, 44(6):304-313. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zgjg201706039
[24]	唐英杰, 马舒庆, 杨玲, 等.云底高度的地基毫米波云雷达观测及其对比.应用气象学报, 2015, 26(6):680-687. doi: 10.11898/1001-7313.20150604
[25]	Holben B, Eck T, Slutsker I, et al.AERONET-A federated instrument network and data archive for aerosol characterization.Remote Sens Environ, 1998, 66:1-16. doi: 10.1016/S0034-4257(98)00031-5
[26]	Chou M, Suarez M.A solar radiation parameterization (CLIRAD-SW) for atmospheric studies.NASA Tech Memo, 1999, 10460:48. http://www.researchgate.net/publication/237129013_A_solar_radiation_parameterization_(CLIR-AD-SW)_for_atmospheric_studies
[27]	沈元芳, 刘洪利, 刘煜, 等.GRAPES紫外线(UV)数值预报.气象科技, 2009, 37(6):697-704. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=qxkj200906012
[28]	颜鹏, 刘桂清, 周秀骥, 等.上甸子秋冬季雾霾期间气溶胶光学特性.应用气象学报, 2010, 21(3):257-265. http://qikan.camscma.cn/article/id/20100301
[29]	杨东贞, 于海青, 丁国安, 等.北京北郊冬季低空大气气溶胶分析.应用气象学报, 2002, 13(增刊Ⅰ):113-126. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=yyqxxb2002z1013
[30]	贾小芳, 颜鹏, 孟昭阳, 等.2016年11-12月北京及周边重污染过程PM_2.5特征.应用气象学报, 2019, 30(3):302-315. doi: 10.11898/1001-7313.20190305
[31]	Petäjä T, Järvi L, Kerminen V, et al.Enhanced air pollution via aerosol-boundary layer feedback in China.Sci Rep, 2016, 6:18998. doi: 10.1038/srep18998
[32]	李成才, 刘启汉, 毛节泰, 等.利用MODIS卫星和激光雷达遥感资料研究香港地区的一次大气气溶胶污染.应用气象学报, 2004, 15(6):641-650. http://qikan.camscma.cn/article/id/20040695
[33]	Liu Q, Ding D, Huang M, et al.A study of elevated pollution layer over the North China Plain using aircraft measurements.Atmos Environ, 2018, 190:188-194. doi: 10.1016/j.atmosenv.2018.07.024
[34]	Sassen K.The Polarization lidar technique for cloud research:A review and current assessment.Bull Amer Meteor Soc, 1992, 72(12):1848-1866. https://journals.ametsoc.org/bams/article/72/12/1848/53807/The-Polarization-Lidar-Technique-for-Cloud
[35]	Che H, Zhao H, Wu Y, et al.Analyses of aerosol optical properties and direct radiative forcing over urban and industrial regions in Northeast China.Meteor Atmos Phys, 2015, 127(3):345-354. doi: 10.1007/s00703-015-0367-3
[36]	车慧正, 张小曳, 石广玉, 等.沙尘和灰霾天气下毛乌素沙漠地区大气气溶胶的光学特征.中国粉体技术, 2005, 11(3):4-7. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zgftjs200503002
[37]	杨先逸, 车慧正, 陈权亮, 等.天空辐射计观测反演北京城区气溶胶光学特性.应用气象学报, 2020, 31(3):373-384. doi: 10.11898/1001-7313.20200311
[38]	王跃思, 辛金元, 李占清, 等.中国地区大气气溶胶光学厚度与Ångström参数联网观测(2004-08-2004-12).环境科学, 2006, 27(9):1703-1711. http://d.wanfangdata.com.cn/Periodical/hjkx200609002
[39]	Ångström.The parameters of atmospheric turbidity.Tellus, 1964, 16:64-75. doi: 10.3402/tellusa.v16i1.8885?src=recsys
[40]	杨溯, 石广玉, 王标, 等.气溶胶光学厚度谱特征判断粒子大小方法初探.应用气象学报, 2011, 22(2):152-157. http://qikan.camscma.cn/article/id/20110204