基于成都市2017年10~12月逐时大气能见度和相对湿度观测资料,结合同时次黑碳(BC)、颗粒物(PM)以及二氧化氮(NO2)质量浓度数据,利用相关性分析、方差膨胀因子法以及GAM模型分析了气溶胶消光系数对多因素变化的响应关系.结果表明:气溶胶消光系数的解释变量集包括ρPM2.5、RH、ρBC/ρPM2.5、ρPM1/ρPM2.5和ρPM2.5/ρPM10(ρBC、ρPM1、ρPM2.5和ρPM10分别为BC、PM1、PM2.5和PM10的质量浓度),各解释变量与气溶胶消光系数均呈现出显著的非线性关系(通过α=0.001的显著性检验).相比于传统气溶胶消光系数双变量模型,以ρPM2.5、RH、ρBC/ρPM2.5、ρPM1/ρPM2.5和ρPM2.5/ρPM10为解释变量的气溶胶消光系数多变量GAM模型显著提升了对气溶胶消光系数的模拟效果,降低了气溶胶消光系数在高湿气象条件下的模拟偏差.对应轻微、轻度、中度和重度霾,GAM模型的调整判定系数(R2)分别为0.659、0.683、0.738和0.938,决定系数(R2)分别为0.686、0.737、0.777和0.961,平均相对误差(MRE)分别为0.091、0.041、0.071和0.016.上述成果揭示了气溶胶消光系数多因素影响的复杂性及其与霾强度变化的内在联系.
Abstract
Using the hourly atmospheric visibility and relative humidity observations in Chengdu from October to December 2017, along with simultaneous data of black carbon (BC), particulate matter (PM), and nitrogen dioxide (NO2) mass concentrations, the response of aerosol extinction coefficients to the changes of multiple factors was analyzed through correlation analysis, variance inflation factor analysis and the GAM model. The results revealed that the explanatory variable set for aerosol extinction coefficients included ρPM2.5, RH, ρBC/ρPM2.5, ρPM1/ρPM2.5, and ρPM2.5/ρPM10 (where ρBC, ρPM1, ρPM2.5, and ρPM10 represent the mass concentrations of BC, PM1, PM2.5, and PM10, respectively). Each variable demonstrated a significant nonlinear relationship with aerosol extinction coefficients. Compared to traditional bivariate models, the multivariate GAM model incorporating ρPM2.5, RH, ρBC/ρPM2.5, ρPM1/ρPM2.5, and ρPM2.5/ρPM10 as explanatory variables significantly improved simulation accuracy, particularly in reducing high-humidity-related biases. The adjusted R2 values of the GAM models were 0.659, 0.683, 0.738, and 0.938 for slight, light, moderate, and heavy haze conditions, respectively. The coefficient of determination (R2) values were 0.686, 0.737, 0.777, and 0.961, with mean relative errors (MRE) of 0.091, 0.041, 0.071, and 0.016. The above results revealed the complexity of the multifactorial influence of the aerosol extinction coefficient and its intrinsic relationship with the change of haze intensity.
关键词
气溶胶消光系数 /
解释变量集 /
广义可加模型 /
霾 /
成都
Key words
aerosol extinction coefficient /
explanatory variable dataset /
GAM /
haze /
Chengdu
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1] 张小曳.中国大气气溶胶及其气候效应的研究 [J]. 地球科学进展, 2007,(1):12-16. Zhang X Y. Aerosol over China and their climate effect [J]. Advances In Earth Science, 2007,(1):12-16.
[2] 韦莲芳,杨复沫,谭吉华,等.大气气溶胶消光性质的研究进展 [J]. 环境化学, 2014,33(5):705-715. Wei L F, Yang F M, Tan J H, et al. Research progress on aerosol extinction properties [J]. Environmental Chemistry, 2014,33(5):705- 715.
[3] 李学彬,徐青山,魏合理,等.气溶胶消光系数与质量浓度的相关性研究 [J]. 光学学报, 2008,(9):1655-1658. Li X B, Xu Q S, Wei H L, et al. Study on relationship between extinction coefficient and mass concentration [J]. Acta Optica Sinica, 2008,(9):1655-1658.
[4] Pitchford M, Maim W, Schichtel B, et al. Revised algorithm for estimating light extinction from IMPROVE particle speciation data [J]. Journal of the Air & Waste Management Association, 2007,57(11): 1326-1336.
[5] 姚婷婷,黄晓锋,何凌燕,等.深圳市冬季大气消光性质与细粒子化学组成的高时间分辨率观测和统计关系研究 [J]. 中国科学:化学, 2010,40(8):1163-1171. 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]. Scientia Sinica Chimica, 2010,40(8):1163-1171.
[6] 宋 宇,唐孝炎,张远航,等.北京市大气能见度规律及下降原因 [J]. 环境科学研究, 2003,(2):10-12. Song Y, Tang X Y, Zhang Y H, et al. The study of the status and degradation of visibility in Beijing [J]. Research of Environmental Sciences, 2003,(2):10-12.
[7] 张智察,倪长健,张城语,等.气溶胶粒径吸湿增长与散射吸湿增长的关系 [J]. 中国环境科学, 2020,40(12):5198-5204. Zhang Z C, Ni C J, Zhang C Y, et al. Relationship between particle size hygroscopic growth and scattering hygroscopic growth [J]. China Environmental Science, 2020,40(12):5198-5204.
[8] 刘新罡,张远航.大气气溶胶吸湿性质国内外研究进展 [J]. 气候与环境研究, 2010,15(6):808-816. Liu X G, Zhang Y H. Advances in research on aerosol hygroscopic properties at home and abroad [J]. Climatic and Environmental Research, 2010,15(6):808-816.
[9] Pilinis C, Seinfeld J H, Grosjean D. Water content of atmospheric aerosols [J]. Atmos. Environ., 1989,23:1601-1606.
[10] 刘 凡,谭钦文,江 霞,等.成都市冬季相对湿度对颗粒物浓度和大气能见度的影响 [J]. 环境科学, 2018,39(4):1466-1472. Liu F, Tan Q W, Jiang X, et al. Effect of relative humidity on particulate matter concentration and visibility during winter in Chengdu [J]. Environmental Science, 2018,39(4):1466-1472.
[11] Chen J, Zhao C S, Ma N, et al. Aerosol hygroscopicity parameter derived from the light scattering enhancement factor measurements in the North China Plain [J]. Atmospheric Chemistry and Physics, 2014, 14(15):8105-8118.
[12] Xu J, Bergin M H, Yu X, et al. Measurement of aerosol chemical, physical and radiative properties in the Yangtze delta region of China [J]. Atmospheric Environment, 2002,36(2):161-173.
[13] Liu X G, Cheng Y F, Zhang Y H, et al. Influences of relative humidity and particle chemical composition on aerosol scattering properties during the 2006 PRD campaign [J]. Atmospheric Environment, 2008, 42(7):1525-1536.
[14] Cui H, Wang J, Liu T, et al. Spatial and seasonal patterns of dissolved organic matter hydrophobicity in Lake Taihu revealed by the aqueous two-phase system [J]. Science of the Total Environment, 2021,776.
[15] Lowenthal D H, Rogers C F, Saxena P, et al. Sensitivity of estimated light extinction coefficients to model assumptions and measurement errors [J]. Atmospheric Environment, 1995,29(7):751-766.
[16] 张智察,倪长健,赵军平,等.耦合气溶胶双参数化方案的大气能见度数值改进算法 [J]. 中国环境科学, 2021,41(11):5009-5018. Zhang Z C, Ni C J, Zhao J P, et al. An improved numerical algorithm for simulating atmosphere visibility by coupling two aerosol parameterization schemes [J]. China Environmental Science, 2021, 41(11):5009-5018.
[17] Ma N, Zhao C S, Nowak A, et al. Aerosol optical properties in the North China Plain during HaChi campaign: an in-situ optical closure study [J]. Atmospheric Chemistry and Physics, 2011,11(12):5959- 5973.
[18] 陈一娜,赵普生,何 迪,等.北京地区大气消光特征及参数化研究 [J]. 环境科学, 2015,36(10):3582-3589. Chen Y N, Zhao P S, He D, et al. Characteristics and parameterization for atmospheric extinction coefficient in Beijing [J]. Environmental Science, 2015,36(10):3582-3589.
[19] 张智察,倪长健,汤津赢,等.“干”气溶胶等效复折射率与其质量浓度指标的相关性研究 [J]. 光学学报, 2019,39(5):17-24. Zhang Z C, Ni C J, Tang J Y, et al. Correlation between equivalent complex refraction index of "dry" aerosol and its mass concentration index [J]. Acta Optica Sinica, 2019,39(5):17-24.
[20] 米家媛,李 娜,佟景哲,等.气溶胶粒径吸湿增长因子的机器学习模型 [J]. 中国环境科学, 2024,44(2):638-645. Mi J Y, Li N, Tong J Z, et al. Machine learning models for aerosol particle size hygroscopic growth factor [J]. China Environmental Science, 2024,44(2):638-645.
[21] 佟景哲,倪长健,杜云松,等.成都气溶胶散射吸湿增长因子多变量影响分析 [J]. 生态与农村环境学报, 2022,38(5):636-644. Tong J Z, Ni C J, Du Y S, et al. Impact analysis of multivariable of aerosol scattering hygroscopic growth factor in Chengdu [J]. Journal of Ecology and Rural Environment, 2022,38(5):636-644.
[22] 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, 1985,19(4): 669-680.
[23] 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. Yang Y S, Ni C J, Deng Y, et al. Characteristics of atmospheric extinction coefficient and its components in winter in Chengdu [J]. Acta Scientiae Circumstantiae, 2019,39(5):1425-1432.
[24] Cheng Y F, Eichler H, Wiedensohler A, et al. Mixing state of elemental carbon and non-light-absorbing aerosol components derived from in situ particle optical properties at Xinken in Pearl River Delta of China [J]. Journal of Geophysical Research-Atmospheres, 2006,111(D20).
[25] 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. Liu X G, Zhang Y H, Zeng L M, et al. Research on the influential factor of visibility reduction in Guangzhou [J]. Climatic and Environmental Research, 2006,(6):733-738.
[26] 黄聪聪,马 嫣,郑 军.南京冬季气溶胶光学特性及黑碳光吸收增强效应 [J]. 环境科学, 2018,39(7):3057-3066. Huang C C, Ma Y, Zheng J. Aerosol optical properties and light absorption enhancement of EC during wintertime in Nanjing [J]. Environmental Science, 2018,39(7):3057-3066.
[27] 佟景哲,米家媛,涂朝勇,等.霾过程黑碳对气溶胶散射吸湿增长的影响 [J]. 中国环境科学, 2024,44(9):4835-4843. Tong J Z, Mi J Y, Tu C Y, et al. Black carbon during haze processes impact on aerosol scattering hygroscopic growth [J]. China Environmental Science, 2024,44(9):4835-4843.
[28] 佟景哲,倪长健,米家媛,等.气溶胶散射吸湿增长因子的BP神经网络模型 [J]. 环境工程, 2023,41(7):131-137. Tong J Z, Ni C J, Mi J Y, et al. A BP neural network model of aerosol scattering hygroscopic growth factor [J]. Environmental Engineering, 2023,41(7):131-137.
[29] 米家媛,邓 也,李昕翼,等.霾过程气溶胶吸湿参数变化的多因素影响分析 [J]. 中国环境科学, 2025,45(3):1210-1217. Mi J Y, Deng Y, Li X Y, et al. Multifactorial impact analysis of aerosol hygroscopic parameters during haze process [J]. China Environmental Science, 2025,45(3):1210-1217.
[30] Mukaka M M. A guide to appropriate use of correlation coefficient in medical research [J]. Malawi Medical Journal, 2012,24(3):69-71.
[31] 安俊琳,王跃思,朱 彬.主成分和回归分析方法在大气臭氧预报的应用—以北京夏季为例 [J]. 环境科学学报, 2010,30(6):1286-1294. An J L, Wang Y S, Zhu B. Principal component and multiple regression analysis predicting ozone concentrations: Case study in summer in Beijing [J]. Acta Scientiae Circumstantiae, 2010,30(6): 1286-1294.
[32] Tu J, Xia Z, Wang H, et al. Temporal variations in surface ozone and its precursors and meteorological effects at an urban site in China [J]. Atmospheric Research, 2007,85(3/4):310-337.
[33] 谭天怡,郭 松,吴志军,等.老化过程对大气黑碳颗粒物性质及其气候效应的影响 [J]. 科学通报, 2020,65(36):4235-4250. Tan T Y, Guo S, Wu Z J, et al. Impact of aging process on atmospheric black carbon aerosol properties and climate effects [J]. Chinese Science Bulletin, 2020,65(36):4235-4250.
基金
国家重点研发计划(2023YFC3709301);四川省科技教育联合基金项目(2024NSFSC1983)
PDF(1028 KB)
京公网安备 11010802030352号 
