基于机器学习算法的干旱区挥发性有机物分布特征及其对臭氧形成的多维影响

IF 7.3 2区环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES

Environmental Pollution Pub Date : 2025-03-27 DOI:10.1016/j.envpol.2025.126159

Guangyao Shi , Huihui Du , Lingtong Du , Xilu Ni , Yang Hu , Danbo Pang , Liangjin Yao

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引用次数: 0

摘要

挥发性有机化合物（VOCs）是大气污染的关键成分，在臭氧（O3）的形成中起着关键作用。了解VOCs的分布和污染源对把握VOCs对O3产生的多方面影响至关重要。本研究在银川市城市生态系统研究站开展了VOCs、气象因子和O3的同步野外观测。采用机器学习算法对VOCs污染源进行分析，并评价其对O3形成的影响。结果表明：夏季高海拔地区总VOCs月平均体积分数为29.28×10-9，以烷烃为主，占总VOCs的51.1%；乙烷（3.55×10-9）、正己烷（3.36×10-9）和丙烷（2.85×10-9）被确定为关键成分。人工源对夏季VOCs排放的贡献率为78.6%，其中烃类挥发性排放源（31.6%）和机动车排放源（30.1%）为主要排放源，自然排放源仅占21.4%。VOCs对O3水平有显著的负影响，总效应值为-0.29。在VOCs组分中，芳烃、卤代烃和烷烃是O3动态的主要影响因子，其影响值分别为0.84、0.75和0.71，贡献率分别为21.8%、19.4%和18.4%。在气象因子中，温度是O3水平的关键决定因素，具有显著的正向影响（效应值为0.58）。温度、风速和相对湿度主要通过直接效应影响O3，光合有效辐射主要通过影响VOCs间接影响O3。研究结果将污染源、气象因素和空气质量管理联系起来。通过系统的多维度分析，更深入地了解高海拔地区气象因子、VOCs和O3之间的复杂关系。这些见解为制定精确的、特定区域的、针对不同成分的空气污染控制措施提供了科学依据。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Distribution characteristics of volatile organic compounds and its multidimensional impact on ozone formation in arid regions based on machine learning algorithms

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Distribution characteristics of volatile organic compounds and its multidimensional impact on ozone formation in arid regions based on machine learning algorithms

Volatile Organic Compounds (VOCs) are key components of atmospheric pollution and play a critical role in ozone (O₃) formation. Understanding their distribution and pollution sources is essential to grasping the multifaceted impact of VOCs on O₃ production. This study, conducted at the Yinchuan Urban Ecosystem Research Station, carried out simultaneous field observations to collect data on VOCs, meteorological factors, and O₃. Machine learning algorithms were employed to analyze the sources of VOCs pollution and evaluate their impact on O₃ formation. Results show that the monthly average volume fraction of total VOCs was 29.28 × 10⁻⁹, with alkanes dominating, accounting for 51.1 % of total VOCs during summer at high altitudes. Ethane (3.55 × 10⁻⁹), n-hexane (3.36 × 10⁻⁹), and propane (2.85 × 10⁻⁹) were identified as key components. Artificial source contributed 78.6 % of VOCs emissions in summer, with hydrocarbon volatile emission source (31.6 %) and vehicle emission source (30.1 %) being the major sources, while natural emissions accounted for only 21.4 %. VOCs exhibited a notable negative impact on O₃ levels, reflected by a total effect value of −0.29. Among the VOCs components, aromatics, halocarbons, and alkanes were identified as the primary contributors to O₃ dynamics, with respective effect values of 0.84, 0.75, and 0.71, and their contribution rates were quantified as 21.8 %, 19.4 %, and 18.4 %, respectively. Among meteorological factors, temperature was a key determinant of O₃ levels, with a significant positive effect (effect value of 0.58). Temperature, wind speed, and relative humidity primarily influenced O₃ through direct effects, while photosynthetically active radiation indirectly influenced O₃ by affecting VOCs. The findings of this study link pollution sources, meteorological factors, and air quality management. Through systematic multidimensional analysis, it offers deeper insights into the complex relationships between meteorological factors, VOCs, and O₃ in high-altitude areas. These insights provide a scientific basis for formulating precise, region-specific, and component-targeted air pollution control measures.

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来源期刊

Environmental Pollution 环境科学-环境科学

CiteScore

16.00

自引率

6.70%

发文量

2082

审稿时长

2.9 months

期刊介绍： Environmental Pollution is an international peer-reviewed journal that publishes high-quality research papers and review articles covering all aspects of environmental pollution and its impacts on ecosystems and human health. Subject areas include, but are not limited to: • Sources and occurrences of pollutants that are clearly defined and measured in environmental compartments, food and food-related items, and human bodies; • Interlinks between contaminant exposure and biological, ecological, and human health effects, including those of climate change; • Contaminants of emerging concerns (including but not limited to antibiotic resistant microorganisms or genes, microplastics/nanoplastics, electronic wastes, light, and noise) and/or their biological, ecological, or human health effects; • Laboratory and field studies on the remediation/mitigation of environmental pollution via new techniques and with clear links to biological, ecological, or human health effects; • Modeling of pollution processes, patterns, or trends that is of clear environmental and/or human health interest; • New techniques that measure and examine environmental occurrences, transport, behavior, and effects of pollutants within the environment or the laboratory, provided that they can be clearly used to address problems within regional or global environmental compartments.