AN ATMOSPHERIC EXTINCTION CHARACTERISTICS AND VISIBILITY PREDICTION MODEL FOR TYPICAL HAZE PROCESSES AT AIRPORTS

ZHENG Chen; WANG Xuan; WANG Lijie; MA Simeng; HAN Bo

doi:10.13205/j.hjgc.202403027

Volume 42 Issue 3

Mar. 2024

Turn off MathJax

Article Contents

Article Navigation > ENVIRONMENTAL ENGINEERING > 2024 > 42(3): 215-224

ZHENG Chen, WANG Xuan, WANG Lijie, MA Simeng, HAN Bo. AN ATMOSPHERIC EXTINCTION CHARACTERISTICS AND VISIBILITY PREDICTION MODEL FOR TYPICAL HAZE PROCESSES AT AIRPORTS[J]. ENVIRONMENTAL ENGINEERING , 2024, 42(3): 215-224. doi: 10.13205/j.hjgc.202403027

Citation:

ZHENG Chen, WANG Xuan, WANG Lijie, MA Simeng, HAN Bo. AN ATMOSPHERIC EXTINCTION CHARACTERISTICS AND VISIBILITY PREDICTION MODEL FOR TYPICAL HAZE PROCESSES AT AIRPORTS[J]. ENVIRONMENTAL ENGINEERING , 2024, 42(3): 215-224. doi: 10.13205/j.hjgc.202403027

Citation:

PDF( 11320 KB)

AN ATMOSPHERIC EXTINCTION CHARACTERISTICS AND VISIBILITY PREDICTION MODEL FOR TYPICAL HAZE PROCESSES AT AIRPORTS

doi: 10.13205/j.hjgc.202403027

ZHENG Chen^1,2,
WANG Xuan^1,2,
WANG Lijie^2,3,
MA Simeng^1,2,
HAN Bo^{1,2
,
,}

1. School of Transportation Science and Engineering, Civil Aviation University of China, Tianjin 300300, China;
2. Research Centre for Environment and Sustainable Development of Civil Aviation Administration of China, Tianjin 300300, China;
3. Airport Operation Center, Jinan International Airport Company Limited, Jinan 250107, China

Received Date: 2023-02-04
Available Online: 2024-05-31

Abstract

Abstract

Atmospheric visibility is one of the most important indicators of airport operations, and it is vital to investigate the mechanism of low visibility weather formation at airports and to accurately predict visibility trends for the safe and efficient operation of air traffic. By monitoring the atmospheric optical parameters, pollutant concentrations, and meteorological conditions at Tianjin Airport, we studied the extinction characteristics of the airport atmosphere during typical haze weather from 8th to 23rd December 2020, constructed airport visibility prediction models based on the generalized additive model (GAM) and the gradient boost regression tree (GBRT) respectively, and compared the prediction results to determine the optimal model. The results indicated that during a typical winter haze pollution-induced low visibility at Tianjin Airport, the B_ext ranged from 37.4 Mm^-1 to 891.7 Mm^-1, with a mean value of 346.0 Mm^-1. The contributions of B_sp, B_ap, B_ag, and B_sg to B_ext respectively accounted for 73.7%, 11.7%, 5.9%, and 8.7%, with aerosol pollution being the visibility reduction, and GBRT analysis showed that the relative contribution of particles below 1 μm to total extinction was the largest. Meanwhile, BC and NO₂ can also reduce visibility through extinction. Using meteorological parameters and pollutant concentration data, both the GAM and GBRT models can provide more accurate prediction on airport visibility, and the GBRT model fitting better than the GAM model, indicating that the GBRT model can provide accurate and reliable airport visibility predictions in frequent haze weather.
- airport pollution,
- atmospheric extinction characteristics,
- low visibility prediction,
- GAM,
- GBRT

FullText(HTML)

References(31)

References

[1]	LACK D A, CAPPA C D. Impact of brown and clear carbon on light absorption enhancement, single scatter albedo and absorption wavelength dependence of black carbon[J]. Atmospheric Chemistry and Physics, 2010, 10(9):4207-4220.
[2]	HAN B, WANG L, DENG Z, et al. Source emission and attribution of a large airport in Central China[J]. Science of the Total Environment, 2022, 829:154519.
[3]	王琼,毕晓辉,张裕芬,等.杭州市大气颗粒物消光组分的粒径分布特征研究[J].中国环境科学,2012,32(1):10-16.
[4]	姚青,韩素芹,蔡子颖,等.天津城区春季大气气溶胶消光特性研究[J].中国环境科学,2012,32(5):795-802.
[5]	VECCHI R, BERNARDONI V, VALENTINI S, et al. Assessment of light extinction at a European polluted urban area during wintertime:impact of PM₁ composition and sources[J]. Environmental Pollution, 2018, 233:679-689.
[6]	ZHU L, ZHU G, HAN L, et al. The application of deep learning in airport visibility forecast[J]. Atmospheric and Climate Sciences, 2017, 7(3):314.
[7]	WON W S, OH R, LEE W, et al. Impact of fine particulate matter on visibility at incheon international airport, South Korea[J]. Aerosol and Air Quality Research, 2020, 20(5):1048-1061.
[8]	ZHANG J, ZHAO P, WANG X, et al. Main factors influencing winter visibility at the Xinjin Flight College of the Civil Aviation Flight University of China[J]. Advances in Meteorology, 2020.
[9]	刘旗洋,乔枫雪,陈博,等.不同场景下的交通能见度估算模型的应用[J].大气科学学报,2022,45(2):179-190.
[10]	YAO T T, HUANG X F, HE L Y, et al. High time resolution observation and statistical analysis of atmospheric light extinction properties and the chemical speciation of fine particulates[J]. Science China Chemistry, 2010, 53(8):1801-1808.
[11]	CICHOWICZ R., WIELGOSI?SKI G., FETTER W. Dispersion of atmospheric air pollution in summer and winter season[J]. Environmental Monitoring and Assess, 2017, 189(12):605.
[12]	中国民用航空局. 2019年民航机场生产统计公报[R].中国民用航空局.2020.03.09.
[13]	何镓祺,于兴娜,朱彬,等.南京冬季气溶胶消光特性及霾天气低能见度特征[J].中国环境科学, 2016(6):1645-1653.
[14]	PENNDORF R. Tables of the refractive index for standard air and the Rayleigh scattering coefficient for the spectral region between 0.2 and 20.0 μ and their application to atmospheric optics[J]. Josa, 1957, 47(2):176-182.
[15]	SLOANE C S, WOLFF G T. Prediction of ambient light scattering using a physical model responsive to relative humidity:validation with measurements from Detroit[J]. Atmospheric Environment (1967), 1985, 19(4):669-680.
[16]	BERGSTROM R W, RUSSELL P B, Hignett P. Wavelength dependence of the absorption of black carbon particles:predictions and results from the TARFOX experiment and implications for the aerosol single scattering albedo[J]. Journal of the Atmospheric Sciences, 2002, 59(3):567-577.
[17]	吴兑,毛节泰,邓雪娇,等.珠江三角洲黑碳气溶胶及其辐射特性的观测研究[J].中国科学, 2009, 39(11):1542-1553.
[18]	HANSEN A D A, ROSEN H, NOVAKOV T. The aethalometer-an instrument for the real-time measurement of optical absorption by aerosol particles[J]. Science of the Total Environment, 1984, 36:191-196.
[19]	CURTO J D, PINTO J C. The corrected vif (cvif)[J]. Journal of Applied Statistics, 2011, 38(7):1499-1507.
[20]	HASTIE T J, TIBSHIRANI R J. Generalized additive models Monographs on statistics and applied probability[J]. Chapman & Hall, 1990, 43:335.
[21]	韩博,姚婷玮,王立婕,等.天津机场区域大气NO₂及O₃影响因子研究[J].中国环境科学, 2020, 40(6):2398-2408.
[22]	JACKSON L S, CARSLAW N, CARSLAW D C, et al. Modelling trends in OH radical concentrations using generalized additive models[J]. Atmospheric Chemistry and Physics, 2009, 9(6):2021-2033.
[23]	FRIEDMAN J H. Greedy function approximation:a gradient boosting machine[J]. Annals of Statistics, 2001, 29(5):1189-1232.
[24]	刘新罡,张远航,曾立民,等.广州市大气能见度影响因子的贡献研究[J].气候与环境研究, 2006(6):733-738.
[25]	杨寅山,倪长健,邓也,等.成都市冬季大气消光系数及其组成的特征研究[J].环境科学学报, 2019, 39(5):1425-1432.
[26]	ZHU J, CHEN L, LIAO H, et al. Correlations between PM_2.5 and ozone over China and associated underlying reasons[J]. Atmosphere, 2019, 10(7):352.
[27]	杜川利,余兴,李星敏,等.西安泾河夏季黑碳气溶胶及其吸收特性的观测研究[J].中国环境科学, 2013, 33(4):613-622.
[28]	BARBER P W. Absorption and scattering of light by small particles[J]. Journal of Colloid & Interface Science, 1984, 98(1):290-291.
[29]	曹双. 南京北郊大气气溶胶的粒径分布和消光特性研究[D].南京:南京信息工程大学,2016.
[30]	YAN S, ZHENG Y, CHEN Y, et al. Atmospheric visibility prediction based on multi-model fusion[C]//2021 International Conference on Image, Video Processing, and Artificial Intelligence, SPIE, 2021, 12076:168-175.
[31]	余东昌, 赵文芳, 聂凯, 等. 基于LightGBM算法的能见度预测模型[J]. 计算机应用, 2021, 41(4):1035-1041.