大气与环境光学学报 ›› 2026, Vol. 21 ›› Issue (4): 616-636.doi: 10.3969/j.issn.1673-6141.2026.04.008

• 环境光学监测技术 • 上一篇    

2023年西安市夏季VOCs浓度变化及影响因素分析

吴雅睿 *, 刘双悦 , 徐鏖   

  1. 西安科技大学测绘科学与技术学院, 陕西 西安 710054
  • 收稿日期:2024-06-28 修回日期:2024-11-08 接受日期:2024-11-08 出版日期:2026-07-28 发布日期:2026-07-28
  • 通讯作者: wuyarui@xust.edu.cn E-mail:wuyarui@xust.edu.cn
  • 作者简介:吴雅睿 (1984- ), 女, 河北廊坊人, 博士, 副教授, 主要从事环境监测与治理方面的研究。E-mail: wuyarui@xust.edu.cn
  • 基金资助:
    陕西省教育厅自然科学基金项目 (17JK0494)

Analysis of VOC concentration changes and influencing factors in summer in Xi'an City in 2023

WU Yarui*, LIU Shuangyue, XU Ao   

  1. College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China
  • Received:2024-06-28 Revised:2024-11-08 Accepted:2024-11-08 Online:2026-07-28 Published:2026-07-28
  • Contact: Ya-rui WU E-mail:wuyarui@xust.edu.cn
  • Supported by:
    General Program of National Natural Science Foundation of China

摘要: 为深入研究西安市挥发性有机物 (VOCs) 质量浓度变化特征, 于2023 年6-8 月对西安市城区VOCs展开连续 监测, 采用回归分析、HYSPLIT 轨迹模型和OZIPR模型等方法对该市在观测时段内VOCs质量浓度水平进行了分析, 并结合气象条件和交通数据探究了其影响因素及其对臭氧 (O3) 生成的影响。结果表明: (1) 西安市2023 年夏季VOCs 平均质量浓度为 (3.001 ± 0.634) μg/m3, 其中7、8 月质量浓度明显高于6 月份。同时, VOCs日变化明显,呈现“V”字型 特征, 且与臭氧呈负相关。其中, 早间质量浓度峰值出现在每日08:00 左右, 晚间峰值出现在每日22:00 左右,且晚间 峰值相较于交通高峰具有滞后性, 最低值出现在每日的16:00-18:00 左右。(2) 气象因素对VOCs质量浓度变化的影 响存在差异, 其中温度影响最大, 与VOCs 呈负相关性 (−0.456 < R< −0.617); 其次为相对湿度, 与VOCs 呈正相关性 (−0.486 < R < −0.535); 而风速、降水量与VOCs的相关性最小。机动车排放对西安市2023 年夏季VOCs质量浓度的变 化影响较大, 观测期间西安市城区工作日VOCs质量浓度普遍高于非工作日质量浓度。西安市VOCs与臭氧的生成息 息相关, VOCs高质量浓度日总是伴随着臭氧质量浓度的升高。(3) 后向轨迹聚类结果表明,西安市2023 年夏季气团主 要为中短距离输送, 东南路径气团对西安市城市VOCs影响最大。(4) 经验动力学模拟方法 (EKMA) 曲线结果表明, 西安市夏季臭氧属于VOCs敏感控制区, VOCs排放量的减少能有效降低西安市O3质量浓度。本研究结果对西安市夏 季VOCs污染特征的认识和空气污染防治具有一定的参考价值。

关键词: 挥发性有机物, 经验动力学模拟方法, 后向轨迹聚类, 气象因素, 臭氧

Abstract: Objective Volatile organic compounds (VOCs) are important precursors of tropospheric ozone (O3) and secondary organic aerosols, playing a critical role in regional atmospheric photochemical pollution. In recent years, with the rapid urbanization and industrial development in Xi'an, China, air pollution problems characterized by increasing O3 concentrations have become increasingly prominent in summer. Therefore, understanding the temporal variation characteristics of VOCs and their relationship with O3 formation is essential for developing effective air pollution control strategies. In this study, continuous monitoring of VOCs was conducted in the urban area of Xi'an during the summer of 2023. The main objectives were to analyze the concentration levels and temporal variation characteristics of VOCs, investigate the influence of meteorological conditions and anthropogenic emissions on VOCs, identify the regional transport pathways of air masses affecting VOCs concentrations, and evaluate the contribution of VOCs to ozone formation. Methods Continuous monitoring data of VOC concentrations in Xi'an from June to August 2023 were collected and analyzed to investigate their temporal variation characteristics. Regression analysis was applied to examine the relationships between VOC concentrations and meteorological factors, including temperature, relative humidity, wind speed, and precipitation. In addition, traffic flow data were introduced to evaluate the influence of motor vehicle emissions on VOC variations in the urban area. To further investigate the regional transport characteristics of air masses affecting VOC concentrations, the HYSPLIT backward trajectory model was used to calculate and cluster the trajectories of air masses arriving in Xi'an during the observation period. Meanwhile, the OZIPR photochemical model was applied to analyze the sensitivity relationship between VOCs and nitrogen oxides (NOx) during O3 formation through EKMA curve analysis. By integrating monitoring data, meteorological information, and model simulation results, the study comprehensively assessed the influencing factors of VOC concentrations and their potential impact on O3 formation in Xi'an. Results and Discussion The results showed that the average concentration of VOCs in Xi'an during the summer of 2023 was (3.001 ± 0.634) μg/m³, indicating a relatively high level of VOC pollution in the urban atmosphere. The monthly variation characteristics showed that the VOC concentrations in Xi'an in July and August were significantly higher than those in June, which may be related to higher temperatures and stronger photochemical activity in midsummer. The diurnal variation of VOCs exhibited a pronounced "V"-shaped pattern and showed a negative correlation with ozone concentrations. Specifically, the concentrations of VOCs reached their peaks at approximately 08:00 in the morning and around 22:00 at night. The morning peak was mainly related to the increase of traffic emissions during rush hours and the relatively stable atmospheric conditions that limited the diffusion of pollutants. The nighttime peak occurred after the traffic rush hours, indicating a certain lag effect caused by atmospheric accumulation and reduced boundary layer height during nighttime. The lowest VOC concentrations generally appeared between 16:00 and 18:00, which may be attributed to enhanced atmospheric mixing and stronger photochemical reactions that promote the consumption of VOCs. Meteorological factors exhibited different degrees of influence on VOC concentrations. Among them, temperature showed the strongest correlation with VOC variations, with a significant negative correlation (−0.617 < R < −0.456), indicating that higher temperatures tend to enhance photochemical reactions and accelerate the consumption of VOCs in the atmosphere. Relative humidity also showed a notable correlation with VOC concentrations, generally presenting a positive relationship ( −0.535 < R < −0.486), which suggests that humid conditions may favor the accumulation of VOCs or the reduction of VOC dispersion. In contrast, wind speed and precipitation showed relatively weak correlations with VOC concentrations during the observation period. The analysis of traffic data further indicated that motor vehicle emissions were an important source contributing to VOC variations in Xi'an. The concentrations of VOCs on weekdays were generally higher than those on non-working days, reflecting the significant influence of urban traffic activities on atmospheric VOC levels. Furthermore, the backward trajectory clustering analysis based on the HYSPLIT model indicated that the air masses affecting Xi'an during the summer of 2023 were mainly transported over short and medium distances. Among the identified transport pathways, the air masses originating from the southeast had the greatest impact on urban VOC concentrations in Xi'an, suggesting that regional transportation from surrounding areas may contribute to the accumulation of VOCs in the city. In addition, the EKMA curve analysis based on the OZIPR model showed that O3 formation in Xi'an during summer was in a VOCs-sensitive regime, which indicating that reducing VOC emissions is more effective than reducing NOx emissions in controlling O3 pollution under current atmospheric conditions. The results also highlight the close relationship between VOC concentrations and O3 formation, as an increase in VOC levels is often accompanied by an increase in O3 concentrations. Conclusion This study systematically analyzed the temporal variation characteristics, influencing factors, and regional transport patterns of VOCs in the summer of 2023 in Xi'an City. The results demonstrated that the VOC concentrations exhibited clear diurnal and monthly variation patterns, and were strongly influenced by meteorological conditions and motor vehicle emissions. Regional air mass transport also played an important role in shaping VOC distribution in the urban atmosphere. Moreover, O3 formation in summer 2023 in Xi'an during was primarily controlled by VOCs-sensitive photochemical conditions, indicating that reducing VOCs emissions will be an effective strategy for mitigating O3 pollution. These findings provide important scientific evidence for understanding the characteristics of VOC pollution and valuable support for the formulation of targeted air pollution prevention and control measures in Xi'an.

Key words: volatile organic compounds, empirical kinetic modeling approach (EKMA), backward trajectory clustering; meteorological factor, ozone

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