基于I-CIMS的深圳大气中气态硝酸观测及污染特征分析

焦伯旸, 唐梦雪, 曹礼明, 杨胜奥, 黄晓锋, 何凌燕

中国环境科学 ›› 2025, Vol. 45 ›› Issue (9) : 4807-4814.

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中国环境科学 ›› 2025, Vol. 45 ›› Issue (9) : 4807-4814.
大气污染与控制

基于I-CIMS的深圳大气中气态硝酸观测及污染特征分析

  • 焦伯旸, 唐梦雪, 曹礼明, 杨胜奥, 黄晓锋, 何凌燕
作者信息 +

Gaseous nitric acid observation and contamination characteristic analysis in Shenzhen based on I-CIMS

  • JIAO Bo-yang, TANG Meng-xue, CAO Li-ming, YANG Sheng-ao, HUANG Xiao-feng, HE Ling-yan
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摘要

为探究深圳市大气气态硝酸(HNO3)的污染特征及驱动机制,本研究基于碘离子化学电离飞行时间质谱(I-CIMS)技术,于2023年夏季和2024年冬季开展HNO3观测,结合机器学习探讨其驱动机制.结果显示,冬季HNO3浓度(0.72±0.19)×10-9显著高于夏季(0.09±0.05)×10-9,呈昼高夜低特征.模型拟合良好(R2=0.91),SHAP分析表明温度是首要影响因子,气粒分配主导HNO3变化.温度在夏季影响更为明显,化学过程在冬季影响更显著.氯盐通过置换硝酸盐抑制HNO3生成,揭示氯亏损对氮循环的复杂作用.建议优先控制NH3排放,不仅抑制总硝酸生成也降低HNO3向颗粒相转化,并关注氯亏损对沿海城市氮循环的复杂影响,为珠三角区域硝酸盐污染防控提供科学依据.

Abstract

To investigate the pollution characteristics and driving mechanisms of atmospheric gaseous nitric acid (HNO3) in Shenzhen, this study conducted HNO3 measurements during summer 2023 and winter 2024 using iodide ion chemical ionization time-of-flight mass spectrometry (I-CIMS), combined with machine learning for mechanism analysis. The results revealed significantly higher HNO3 concentrations in winter (0.72±0.19×10-9) compared to summer (0.09±0.05×10-9), with distinct diurnal patterns showing daytime peaks. The model demonstrated good performance (R2=0.91), with SHAP analysis identifying temperature as the primary driver governing HNO3 variation through gas-particle partitioning. Seasonal differences emerged: temperature dominated summer dynamics through thermodynamic control, while chemical processes prevailed in winter. Notably, chloride salts suppressed HNO3 formation through nitrate displacement, revealing the complex role of chloride depletion in nitrogen cycling. Our findings highlight the priority of NH3 emission control, which concurrently inhibits total nitrate formation and reduces HNO3 particle-phase conversion. Special attention should be given to coastal urban nitrogen cycling complexities induced by chloride depletion, providing scientific basis for nitrate pollution mitigation in the Pearl River Delta region.

关键词

气态硝酸(HNO3) / 化学电离飞行时间质谱(CIMS) / 气粒分配 / 机器学习 / SHAP

Key words

gaseous nitric acid (HNO3) / chemical ionization mass (CIMS) / gas-particle partitioning / machine learning / SHAP

引用本文

导出引用
焦伯旸, 唐梦雪, 曹礼明, 杨胜奥, 黄晓锋, 何凌燕. 基于I-CIMS的深圳大气中气态硝酸观测及污染特征分析[J]. 中国环境科学. 2025, 45(9): 4807-4814
JIAO Bo-yang, TANG Meng-xue, CAO Li-ming, YANG Sheng-ao, HUANG Xiao-feng, HE Ling-yan. Gaseous nitric acid observation and contamination characteristic analysis in Shenzhen based on I-CIMS[J]. China Environmental Science. 2025, 45(9): 4807-4814
中图分类号: X51   

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基金

国家自然科学基金资助项目(42407145)

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