霾过程气溶胶吸湿参数变化的多因素影响分析

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摘要基于成都市2017年10~12月的逐时观测数据,以及该时段同时次大气能见度(V)、相对湿度(RH)和二氧化氮(NO₂)监测资料,通过耦合免疫进化算法和Mie散射理论反演气溶胶粒径吸湿增长因子(Gf).利用κ-köhler理论计算气溶胶吸湿参数κ,分析了霾过程气溶胶吸湿参数κ的变化特征及其影响因素.结果表明:轻微、轻度、中度和重度霾强度条件下,气溶胶吸湿参数κ分别为(0.142±0.092)、(0.149±0.088)、(0.191±0.061)和(0.200±0.041).气溶胶吸湿参数κ的解释变量集包括C_BC, C_BC/C_PM_2.5, C_PM1/C_PM_2.5和C_PM_2.5/C_PM₁₀(C_BC、C_PM₁、C_PM_2.5、C_PM₁₀分别为BC、PM₁、PM_2.5、PM₁₀的质量浓度),各变量对气溶胶吸湿参数κ的解释能力随霾强度的变化存在显著的差异.多因素GAM模型可以很好地表征气溶胶吸湿参数κ的变化特征(通过了α=0.01的显著性检验),在轻微、轻度、中度和重度霾条件下,对应的调整判定系数(R²)分别为0.303、0.488、0.504、0.631,压轴回归决定系数(R²)分别为0.327、0.517、0.558、0.739,残差平方和(RSS)分别为1.448、0.721、0.209、0.025.上述成果揭示了气溶胶吸湿参数κ多因素影响的复杂性及其与灰霾演化的内在联系.

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	米家媛
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	倪长健

关键词 ：气溶胶, 吸湿参数, 霾强度, GAM模型, 成都

Abstract：Based on the hourly observational data from October to December 2017 in Chengdu, as well as the simultaneous data of atmospheric visibility (V), relative humidity (RH) and nitrogen dioxide (NO₂), aerosol hygroscopic growth factor (Gf) was retrieved by Mie scattering theory coupled with immune evolutionary algorithm, and then aerosol hygroscopic parameter κ was calculated by κ-köhler theory, the variation characteristics of aerosol hygroscopic parameter κ and its influencing factors were analyzed during the haze process. The results showed that: The aerosol hygroscopic parameters κ were 0.142±0.092、0.149±0.088、0.191±0.061and 0.200±0.041 under mild, light, moderate and heavy haze intensity conditions respectively. The set of explanatory variables of aerosol hygroscopicity parameter κ was determined, including C_BC, C_BC/C_PM_2.5, C_PM₁/C_PM_2.5 and C_PM_2.5/C_PM₁₀ (C_BC, C_PM₁, C_PM_2.5 and C_PM₁₀ represented mass concentrations of BC, PM₁, PM_2.5 and PM₁₀ respectively). There were significant differences in the explanatory power for aerosol hygroscopic parameter κ of each variable as the haze intensities changed. The multifactor GAM model could be well characterized aerosol hygroscopic parameter κ variation (passed the significance test of α=0.001). As to the above four haze conditions, the corresponding adjusted coefficients of determination (R²) were 0.303, 0.488, 0.504 and 0.631, the coefficients of determination (R²) for the regression of the pressure axis were 0.327, 0.517, 0.558 and 0.739, and the residual sum of squares (RSS) were 1.448, 0.721, 0.209, and 0.025, respectively. The above study revealed the complexity of the multifactorial influence on aerosol hygroscopic parameter κ, and further clarified the intrinsic connection between aerosol hygroscopicity and haze evolution.

Key words： aerosol hygroscopicity parameter haze intensities GAM model Chengdu

收稿日期: 2024-08-06

PACS:

X513

基金资助:国家重点研发计划(2023YFC3709301);四川省科技教育联合基金项目(2024NSFSC1983)

作者简介: 米家媛(1999-),女,辽宁锦州人,助理工程师,主要从事大气物理学与大气环境方面研究.发表论文3篇.mijiayuan1999@163.com.

引用本文:

米家媛, 邓也, 李昕翼, 佟景哲, 李娜, 倪长健. 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 Jia-yuan, DENG Ye, LI Xin-yi, TONG Jing-zhe, LI Na, NI Chang-jian. Multifactorial impact analysis of aerosol hygroscopic parameters during haze process. CHINA ENVIRONMENTAL SCIENCECE, 2025, 45(3): 1210-1217.

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http://www.zghjkx.com.cn/CN/ 或 http://www.zghjkx.com.cn/CN/Y2025/V45/I3/1210

[1] Kotchenruther R A, Hobbs P V, Hegg D A. Humidification factors for atmospheric aerosols off the mid-Atlantic coast of the United States[J]. Journal of Geophysical Research Atmospheres, 1999,104(D2):2239-2251.
[2] Pope C A, Dockery D W. Heath effects of fine particulate air pollution:Lines that connect[J]. Air&Waste Management Association, 2006, 56:709-742.
[3] Hand J L, Kreidenweis S M, Sherman D E, et al. Aerosol size distributions and visibility estimates during the Big Bend regional aerosol and visibility observational (BRAVO) study[J]. Atmospheric Environment, 2002,36:5043-5055.
[4] Wang K, Zhang Y, Yahya K, et al. Implementation and initial application of new chemistry-aerosol options in WRF/Chem for simulating secondary organic aerosols and aerosol indirect effects for regional air quality[J]. Atmospheric Environment, 2015,115:716-732.
[5] 张智察,倪长健,邓也,等.免疫进化算法反演均匀混合气溶胶吸湿增长因子[J].中国环境科学, 2020,40(3):1008-1015. Zhang Z C, Ni C J, Deng Y, et al. Retrieval of hygroscopic growth factor of uniformly mixed aerosol particles based on immune evolution algorithm[J]. China Environmental Science, 2020,40(3):1008-1015.
[6] Köhler H. The nucleus in and the growth of hygroscopic droplets[J]. Transactions of the Faraday Society, 1936,32:1152-1161.
[7] Petters M D, Kreidenweis S M. A single parameter representation of hygroscopic growth and cloud condensation nucleus activity[J]. Atmos Chem Phys, 2007,7:1961-1971.
[8] 钟佳利,王炜罡,彭超,等.大气气溶胶吸湿性及其对环境的影响[J].化学进展, 2022,34(4):801-814. Zhong J L, Wang W G, Peng C, et al. Atmospheric aerosol hygroscopicity and their influenceon environment[J]. Progress in Chemistry, 2022,34(4):801-814.
[9] Kim N,Park M,Yum S S, et al. Impact of urban aerosol properties on cloud condensation nuclei (CCN) activity during the KORUS-AQ field campaign[J].Atmospheric Environment, 2018:185221-236.
[10] Thalman R, Sa D S S, Palm B B, et al. CCN activity and organic hygroscopicity of aerosols downwind of an urban region in central Amazonia:Seasonal and diel variations and impact of anthropogenic emissions[J]. Atmospheric Chemistry and Physics, 2017,17(19):11779-11801.
[11] Phillips B N, Royalty T M, Dawson K W, et al. Hygroscopicity-and size-resolved measurements of submicron aerosol on the east coast of the United States[J]. Journal of Geophysical Research:Atmospheres, 2018,123(3):1826-39.
[12] Lange R, Dall'Osto M, Wex H, et al. Large summer contribution of organic biogenic aerosols to Arctic cloud condensation nuclei[J]. Geophysical Research Letters, 2019,46(20):11500-11509.
[13] Wu Z, Zheng J, Wang Y, et al. Chemical and physical properties of biomass burning aerosols and their CCN activity:A case study in Beijing, China[J]. Science of the Total Environment, 2017,579:1260-1268.
[14] 高颖,王玉莹,李占清,等.北京和邢台新粒子生成的差别及其对CCN活性的影响[J].大气科学, 2022,46(5):1087−1097. Gao Y, Wang Y Y, Li Z Q, et al. Differences in the effects of new particle formation on cloud condensation nuclei activity in Beijing and Xingtai[J]. Chinese Journal of Atmospheric Sciences, 2022,46(5):1087−1097.
[15] 权建农,徐祥德,贾星灿,等.影响我国霾天气的多尺度过程[J].科学通报, 2020,65(9):810-824. Quan J N, Xu X D, Jia X C, et al. Multi-scale processes in severe haze events in China and their interactions with aerosols:Mechanisms and progresses[J]. Chinese Science Bulletin, 2020,65(9):810-824.
[16] McMurry PH, Wilson JC. Droplet phase (heterogeneous) and gas phase (homogeneous) contributions to secondary ambient aerosol formation as functions of relative humidity[J]. Journal of Geophysical Research:Oceans, 1983,88(C9):5101-5108.
[17] QX/T 113-2010霾的观测和预报等级[S]. QX/T 113-2010 Observation and forecasting levels of haze[S].
[18] 贺祥,林振山.基于GAM模型分析影响因素交互作用对PM_2.5浓度变化的影响[J].环境科学, 2017,38(1):22-32. He X, Lin Z S. Interactive effects of the influencing factors on the changes of PM_2.5 concentration based on GAM Model[J]. Environmental Science, 2017,38(1):22-32.
[19] Köhler H. The nucleus in and the growth of hygroscopic droplets[J]. Transactions of the Faraday Society, The Royal Society of Chemistry, 1936,32(0):1152-1161.
[20] Gysel M, Crosier J, Topping D O, et al. Closure study between chemical composition and hygroscopic growth of aerosol particles during TORCH2[J]. Atmospheric Chemistry and Physics, 2007,7(112):6131-6144.
[21] 石磊,徐明伟.计量检定中的异常值及其剔除方法[J].黑龙江气象, 2006,(4):25-26. Shi L, Xu M W. Anomaly data measured and rejected in quality check-up[J]. Heilongjiang Meteorology, 2006,(4):25-26.
[22] Kim J, Yoon S, Jefferson A, et al. Aerosol hygroscopic properties during Asian dust, pollution, and biomass burning episodes at Gosan, Korea in April 2001[J]. Atmospheric Environment, 2006,40(8):1550-1560.
[23] 刘玥晨,吴志军,谭天怡,等.基于实测PM_2.5化学组分估算其有效吸湿参数和含水量:理论模型与实例分析[J].中国科学:地球科学, 2016,46(7):976-985. Liu Y C, Wu Z J, Tan T Y, et al. Estimation of the PM_2.5 effective hygroscopic parameter and water content based on particle chemical composition:Methodology and case study[J]. Science China Earth Sciences, 2016,46(7):976-985.
[24] 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.
[25] 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. Chin Sci Bull, 2020,65:4235-4250.
[26] Zieger P, Fierz-Schmidhauser R, Gysel M, et al. Effects of relative humidity on aerosol light scattering in the Arctic[J]. Atmospheric Chemistry and Physics, 2010,10(8):3875-3890.
[27] 张智察,倪长健,刘新春,等.干气溶胶复折射率的参数化方案[J].中国环境科学, 2021,41(2):580-587. Zhang Z C, Ni C J, Liu X C, et al. Parameterization scheme for dry aerosols complex refractive index[J]. China Environmental Science, 2021,41(2):580-587.
[28] 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.
[29] 米家媛,佟景哲,倪长健,等.气溶胶粒径吸湿增长多因素影响的GAM模型[J].环境科学与技术, 2023,46(6):128-135. Mi J Y, Tong J Z, Ni C J, et al. GAM model for multifactorial effects on aerosol particle size hygroscopic growth[J]. Environmental Science& Technology, 2023,46(6):128-135.
[30] Chen J, Zhao C S, Ma N, et al. A parameterization of low visibilities for hazy days in the North China Plain[J]. Atmospheric Chemistry and Physics, 2012,12(271):4935-4950.
[31] Tu J, Xia Z G, 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):310-337.
[32] Weingartner E, Burtscher H, Baltensperger U. Hygroscopic properties of carbon and diesel soot particles[J]. Atmospheric Environment, 1997,31(15):2311-2327.
[33] Jacobson M. Z. Strong radiative heating due to the mixing state of black carbon in atmospheric aerosols[J]. Nature, 6821,409(6821):695-697.
[34] 张智胜,陶俊,谢绍东,等.成都城区PM_2.5季节污染特征及来源解析[J].环境科学学报, 2013,33(11):2947-2952. Zhang Z S, Tao J, Xie S D, et al. Seasonal variations and source apportionment of PM_2.5 at urban area of Chengdu[J]. Acta Scientiae Circumstantiae, 2013,33(11):2947-2952.35.