广义加性模型研究青岛沿海夏季大气汞的质量浓度变化特征

doi:10.6040/j.issn.1671-9352.0.2025.018

摘要/Abstract

摘要： 为研究青岛沿海大气汞的污染特征,解析污染源和气象条件的影响,于2023年夏季在青岛小麦岛开展了气态总汞(total gaseous mercury, TGM)的在线监测,构建广义加性模型(generalized additive model, GAM),以研究TGM质量浓度与空气污染物浓度和气象参数的线性与非线性关系。结果表明,TGM质量浓度为(2.94±0.75)ng·m^-3,范围为1.74~6.49 ng·m^-3,属中等污染水平。TGM受人为源排放、气象条件以及海陆风因素影响显著。单因素GAM模型结果表明,CO质量浓度、相对湿度(relative humidity, RH)和海平面气压(P0)对TGM质量浓度变化影响较大,且CO和NOx质量浓度与TGM之间呈现递增关系,表明人为源排放对TGM有显著贡献;而RH和P₀与TGM之间呈递减关系,代表有利的气象条件对TGM的稀释或扩散作用。常规污染物-气象参数多因素GAM模型进一步提高拟合效果,对TGM质量浓度变化的解释度达到84.6%。空气污染物质量浓度与风向(wind direction, WD)、RH和边界层高度(boundary layer height, BLH)存在明显的交互作用。本研究可视化定量分析各因素及其交互作用对青岛沿海TGM质量浓度变化的影响,揭示污染传输和气象条件的共同作用,对沿海大气汞循环理解和污染控制有重要意义。

关键词: 大气汞, 广义加性模型, 人为排放, 气象因素, 交互作用

Abstract: To study the characteristics of atmospheric mercury pollution in coastal Qingdao and evaluate the influences of pollution sources and meteorological conditions, an online measurement of total gaseous mercury(TGM)was conducted on Xiaomai Island in Qingdao during the summer of 2023. A generalized additive model(GAM)was constructed to investigate the linear and nonlinear relationships between TGM and air pollutants as well as meteorological parameters. The results showed the mass concentration of TGM was(2.94±0.75)ng·m^-3, within a range of 1.74-6.49 ng·m^-3, indicating a moderate pollution level in China. TGM mass concentrations were significantly affected by anthropogenic emissions, meteorological conditions, and sea-land breezes. In the univariate GAM model results, CO concentration, relative humidity(RH), and sea-level pressure(P₀)had substantial effects on TGM variations. Specifically, CO and NOx mass concentration exhibited increasing relationships with TGM, indicating that anthropogenic emissions significantly contribute to TGM levels. While RH and P₀ showed decreasing relationships, indicating that favorable meteorological conditions contribute to the dilution or dispersion of TGM. Multivariate GAM model incorporating conventional pollutants and meteorological parameters further improved the fitting results, achieving an explanatory power of 84.6% for TGM variations. The interactions between atmospheric pollutants, WD, RH, and boundary layer height(BLH)significantly influenced TGM variability. This study quantitatively visualizes the complex impacts of various factors and their interactions on TGM variations, revealing the combined effects of pollution transport and meteorological conditions, which is critical for understanding the atmospheric mercury cycle and pollution control in coastal areas.

Key words: atmospheric mercury, generalized additive model, anthropogenic emissions, meteorological factors, interaction effects

中图分类号:

X823

王国静,李涛,甄洁博,聂晓玲,巩超凡,王艳. 广义加性模型研究青岛沿海夏季大气汞的质量浓度变化特征[J]. 《山东大学学报(理学版)》, 2025, 60(5): 133-142.

WANG Guojing, LI Tao, ZHEN Jiebo, NIE Xiaoling, GONG Chaofan, WANG Yan. Generalized additive models for characterizing atmospheric mercury mass concentration variations in the coastal area of Qingdao in summer[J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2025, 60(5): 133-142.

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