生态环境学报 ›› 2023, Vol. 32 ›› Issue (2): 341-350.DOI: 10.16258/j.cnki.1674-5906.2023.02.014

• 研究论文 • 上一篇    下一篇

广州典型城市林地对大气颗粒物的削减效应及影响因素

张莉1,2(), 李铖2, 谭皓泽2,3, 韦家怡4, 程炯2, 彭桂香1,*()   

  1. 1.华南农业大学资源环境学院,广东 广州 510642
    2.广东省科学院生态环境与土壤研究所/华南土壤污染控制与修复国家地方联合工程研究中心/广东省农业环境综合治理重点实验室,广东 广州 510650
    3.广州大学地理科学与遥感学院,广东 广州 510006
    4.广东省科学院广州地理研究所/广东省遥感与地理信息应用重点实验室/广东省地理时空大数据工程实验室/广东省地理空间信息技术与应用公共实验室,广东 广州 510070
  • 收稿日期:2022-11-28 出版日期:2023-02-18 发布日期:2023-05-11
  • 通讯作者: *彭桂香(1968年生),女,副教授,博士,研究领域为土壤学。E-mail: gxpeng@scau.edu.cn
  • 作者简介:张莉(1997年生),女(土家族),硕士研究生,研究方向为土壤学和景观生态学。E-mail: 2279290378@qq.com
  • 基金资助:
    国家自然科学基金项目(42071235);国家自然科学基金项目(31970001);广东省科技计划项目(2020B1111530001);广东省科技计划项目(2020B1212060048);广东省科技计划项目(2020GDASYL-20200103084)

Reduction Effect and Influencing Factors of Typical Urban Woodlands on Atmospheric Particulate Matter in Guangzhou

ZHANG Li1,2(), LI Cheng2, TAN Haoze2,3, WEI Jiayi4, CHENG Jiong2, PENG Guixiang1,*()   

  1. 1. College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, P. R. China
    2. National-Regional Joint Engineering Research Center for Soil Pollution Control and Remediation in South China/Guangdong Key Laboratory of Integrated Agro-environmental Pollution Control and Management/Institute of Eco-environmental and Soil Sciences, Guangdong Academy of Sciences, Guangzhou 510650, P. R. China
    3. School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, P. R. China
    4. Key Laboratory of Guangdong for Utilization of Remote Sensing and Geographical Information System/Guangdong Engineering Laboratory for Geographic Spatio-temporal Big Data/Guangdong Open Laboratory of Geospatial Information Technology and Application/Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, P. R. China
  • Received:2022-11-28 Online:2023-02-18 Published:2023-05-11

摘要:

大气颗粒物是城市大气污染的重要来源,威胁着城市居民健康。城市林地在削减大气颗粒物方面扮演着重要角色。但是,不同林分类型对大气颗粒物的削减作用有何差异及其影响因素,有待进一步研究。以广州市白云山风景名胜区和华南国家植物园典型城市林地为例,选取火力楠-灰木莲林(Michelia macclurel-Manglietia glauca)、白千层林(Melaleuca leucadendron L.)、湿地松-山油柑-柯林[Pinus elliottii-Acronychia pedunculata (L.) Miq.-Lithocarpus glaber (Thunb.) Nakai]、尾叶桉林(Eucalyptus urophylla S T Blake)、木荷-锥林(Schima superba Gardn. et Champ.-Castanopsis chinensis (Sprengel) Hance)等5种林分类型,分别对林内外大气颗粒物(TSP、PM10、PM2.5、PM1.0)进行人工对比观测,探讨不同林分类型对大气颗粒物的削减效应,并结合气象因素和林地植被特征,分析削减效应的影响因素。结果表明:(1)总体上,除了(火力楠-灰木莲)林对4种大气颗粒物的削减效率均为负值,其他林分类型对细颗粒物和超细颗粒物(PM2.5和PM1.0)具有正削减效应,对总颗粒物和粗颗粒物(TSP和PM10)具有负削减效应;针阔混交林对大气颗粒物的削减效率显著高于其他阔叶林;(2)不同林分的削减效率,在日尺度上多呈“W”或“V”型,峰值与谷值出现的时间与上班通勤高峰与低谷期重合;(3)城市林地对大气颗粒物的削减效应与气象因素(尤其温度和风速)以及植被特征(如冠幅和叶面积指数)呈显著正/负相关。该研究中细颗粒物(PM2.5和PM1.0)对林外大气含尘量较敏感,与林外大气颗粒物质量浓度呈显著负相关,这可能与细颗粒物更容易达到峰值(或饱和)有关。在高质量林地建设中,可适当增加针叶树种的种植,优先选择叶面积指数较大的物种,增大林地削减大气颗粒物的能力,改善大气环境。

关键词: 大气颗粒物, 城市林地, 削减, 影响因素, PM10, PM2.5

Abstract:

Atmospheric particulate matter is an important source of urban air pollution, threatening the health of urban residents. Urban woodlands play an important role in reducing atmospheric particulate matter. However, the differences in the reduction of atmospheric particulate matter by different stand types and their influencing factors need to be further studied. In this study, we took five typical urban woodlands (i.e., Michelia macclurel-Manglietia glauca woodland, Melaleuca leucadendron L. woodland, Pinus elliottii-Acronychia pedunculata (L.) Miq.-Lithocarpus glaber (Thunb.) Nakai woodland, Eucalyptus urophylla S.T. Blake woodland, and Schima superba Gardn. et Champ.-Castanopsis chinensis (Sprengel) Hance woodland) in Guangzhou as an example. We investigated the interception effects of the five woodlands and analyzed their influencing factors by combing with the meteorological factors and landscape patterns. We found that all the urban woodlands had negative reduction effects on the coarse atmospheric particulate matter (TSP, PM10), while positive reduction effects on the fine particle matter (PM2.5 and PM1.0; except for the Michelia macclurel-Manglietia glauca woodland). The reduction efficiency of coniferous and broadleaf woodland on atmospheric particulate matter was significantly higher than the broad-leaved woodlands. The reduction efficiency of different woodlands showed similar fluctuations on the daily scale, with several peaks and valleys consistent with people’s commute time to work. The reduction effect of urban woodland on atmospheric particulate matter showed significantly positive or negative correlations with the meteorological factors (especially temperature and wind speed) and vegetation characteristics such as crown width and leaf area index. In addition, the fine particles matter (PM2.5 and PM1.0) in this study seemed sensitive to the total atmospheric dust out of the woodland as indicated by showing significant and negative correlations with the particulate matter concentrations out of the woodland. This might be due to the fine particulate matter is more likely to peak (or saturate). We suggested planting more coniferous species in broadleaf woodland to increase the ability of woodland to reduce atmospheric particulate matter and improve the atmospheric environment. Our study has limitations in terms of not considering the impacts of autogenous dust generated by the woodland itself (e.g. the pollen) on the atmospheric particle reduction effects, which needs to be further study.

Key words: Atmospheric particulate matter, urban woodland, influencing factors, reduction effect, PM10, PM2.5

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