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

doi:10.16258/j.cnki.1674-5906.2023.02.014

Ecology and Environment ›› 2023, Vol. 32 ›› Issue (2): 341-350.DOI: 10.16258/j.cnki.1674-5906.2023.02.014

• Research Articles • Previous Articles Next Articles

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. 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
Contact: PENG Guixiang

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.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

通讯作者: 彭桂香
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)

Abstract

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 (PM_2.5 and PM_1.0; 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 (PM_2.5 and PM_1.0) 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, PM_2.5

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、PM_2.5、PM_1.0）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（PM_2.5和PM_1.0）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（PM_2.5和PM_1.0）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, PM_2.5

CLC Number:

X173

ZHANG Li, LI Cheng, TAN Haoze, WEI Jiayi, CHENG Jiong, PENG Guixiang. Reduction Effect and Influencing Factors of Typical Urban Woodlands on Atmospheric Particulate Matter in Guangzhou[J]. Ecology and Environment, 2023, 32(2): 341-350.

张莉, 李铖, 谭皓泽, 韦家怡, 程炯, 彭桂香. 广州典型城市林地对大气颗粒物的削减效应及影响因素[J]. 生态环境学报, 2023, 32(2): 341-350.

Figures/Tables 8

References 56

[1]	BUCCOLIERI R, GROMKE C, SABATINO S D, et al., 2009. Aerodynamic effects of trees on pollutant concentration in street canyons[J]. Science of the Total Environment, 407(19): 5247-5256. DOI URL
[2]	BUCCOLIERI R, SALIM S M, LEO L S, et al., 2011. Analysis of local scale tree-atmosphere interaction on pollutant concentration in idealized street canyons and application to a real urban junction[J]. Atmospheric Environment, 45(9): 1702-1713. DOI URL
[3]	BURNETT R, CHEN H, SZYSZKOWICZ M, et al., 2018. Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter[J]. Proceedings of the National Academy of the United States of America, 115(38): 9592-9597. DOI URL
[4]	CHEN L, GAO S, ZHANG H, et al., 2018. Spatiotemporal modeling of PM_2.5 concentrations at the national scale combining land use regression and Bayesian maximum entropy in China[J]. Environment International, 116: 300-307. DOI URL
[5]	GROMKE C, BUCCOLIERI R, SABATINO S D, et al., 2008. Dispersion study in a street canyon with tree planting by means of wind tunnel and numerical investigations-Evaluation of CFD data with experimental data[J]. Atmospheric Environment, 42(37): 8640-8650. DOI URL
[6]	GROMKE C, JAMARKATTEL N, RUCK B, 2016. Influence of roadside hedgerows on air quality in urban street canyons[J]. Atmospheric Environment, 139: 75-86. DOI URL
[7]	GROMKE C, RUCK B, 2007. Influence of trees on the dispersion of pollutants in an urban street canyon-Experimental investigation of the flow and concentration field[J]. Atmospheric Environment, 41(16): 3287-3302. DOI URL
[8]	HUANG D S, XU J H, ZHAN S Q, 2012. Valuing the health risks of particulate air pollution in the Pearl River Delta, China[J]. Environmental Science & Policy, 15(1): 38-47.
[9]	LARKIN A, DONKELAAR A V, GEDDES J A, et al., 2016. Relationships between changes in urban characteristics and air quality in east asia from 2000 to 2010[J]. Environmental Science & Technology, 50(17): 9142-9149. DOI URL
[10]	LUO X S, BING H J, LUO Z X, et al., 2019. Impacts of atmospheric particulate matter pollution on environmental biogeochemistry of trace metals in soil-plant system: A review[J]. Environmental Pollution, 255(Part 1): 113138. DOI URL
[11]	PUGH T A, MACKENZIE A R, WHYATT J D, et al., 2012. Effectiveness of green infrastructure for improvement of air quality in urban street canyons[J]. Environmental Science & Techology, 46(14): 7692-7699.
[12]	SHI W Z, WONG M S, WANG J Z, et al., 2012. Analysis of airborne particulate matter (PM_2.5) over Hong Kong using remote sensing and GIS[J]. Sensors, 12(6): 6825-6836. DOI PMID
[13]	TURNER J, POND G R, TREMBLAY A, et al., 2021. Risk perception among a lung cancer screening population[J]. Chest, 160(2): 718-730. DOI PMID
[14]	VOS P E, MAIHEU B, VANKERKOM J, et al., 2013. Improving local air quality in cities: to tree or not to tree?[J]. Environmental Pollution, 183: 113-122. DOI PMID
[15]	包红光, 王成, 郄光发, 等, 2016. 城市公园外侧防护林结构对外源PM_2.5的消减作用[J]. 生态环境学报, 25(6): 987-993. DOI
	BAO H G, WANG C, QIE G F, et al., 2016. The effect of forest shelter belt on subduction of PM_2.5 in urban parks[J]. Ecology and Environmental Sciences, 25(6): 987-993.
[16]	陈尖, 黎明, 2011. 广东让森林挺进城市[J]. 中国林业 (4): 18-21.
	CHE J, LI M, 2011. Let the forest advance into the city in Guangdong[J]. Forest of China (4): 18-21.
[17]	陈上杰, 牛健植, 韩旖旎, 等, 2015. 道路绿化带内大气PM_2.5质量浓度变化特征[J]. 水土保持学报, 29(2): 100-105.
	CHEN S J, NIU J Z, HAN Y N, et al., 2015. Characteristics of mass concentration variations of PM_2.5 in the road greenbelts[J]. Journal of Soil and Water Conservation, 29(2): 100-105.
[18]	杜志坚, 2017. 华南植物园迁地植物害虫多样性分析[D]. 广州: 仲恺农业工程学院: 6-7.
	DU Z J, 2017. Analysis on the diversity of pests of ex situ plants in Southern China Botanical Garden[D]. Guangzhou: ZhongKai University of Agriculture and Engineering: 6-7.
[19]	冯海英, 2018. 北京市大气颗粒物浓度与植被空间分布相关性研究[D]. 北京: 北京林业大学:68-69.
	FENG H Y, 2018. Study on correlation between particulate concentration and spatial distribution of vegetation in Beijing[D]. Beijing: Beijing Forestry University:68-69.
[20]	郭二果, 2008. 北京西山典型游憩林生态保健功能研究[D]. 北京: 中国林业科学研究院:36-66.
	GUO E G, 2008. Ecological health effects of typical recreation forests in west mountain of Beijing[D]. Beijing: Chinese Academy of Forestry:36-66.
[21]	郭二果, 王成, 郄光发, 等, 2013. 北方地区典型天气对城市森林内大气颗粒物的影响[J]. 中国环境科学, 33(7): 1185-1198.
	GUO E G, WANG C, QIE G F, et al., 2013. Influence of typical weather conditions on the airborne particulate matters in urban forests in northern China[J]. China Environmental Science, 33(7): 1185-1198.
[22]	黄俊彪, 2013. 广州市典型森林土壤多环芳烃分布及其吸附性能研究[D]. 北京: 中国林业科学研究院:15-16.
	HUANG J B, 2013. Distribution and absorption of polycyclic aromatic hydrocarbons in tipical forest soil of Guangzhou[D]. Beijing: Chinese Academy of Forestry:15-16.
[23]	蒋燕, 陈波, 鲁绍伟, 等, 2016. 北京城市森林PM_2.5质量浓度特征及影响因素分析[J]. 生态环境学报, 25(3): 447-457. DOI
	JIANG Y, CHEN B, LU S W, et al., 2016. Analysis on characteristics and influential factors of PM_2.5 mass concentration in Beijing’s urban forest[J]. Ecology and Environmental Sciences, 25(3): 447-457.
[24]	赖乃揆, 翟月明, 贺紫兰, 等, 1982. 广州市部分地区空气中花粉及其致敏性的初步调查[J]. 广州医学院学报 (3): 1-11.
	LAI N K, ZHAI Y M, HE Z L, et al., 1982. Pollen in air in some areas of Guangzhou preliminary investigation of its sensitization[J]. Academic Journal of Guangzhou Medical College (3): 1-11.
[25]	李惠玲, 何秉宇, 玉米提·哈力克, 等, 2020. 干旱区城市森林大气颗粒物浓度变化特征及其与环境因子的关系[J]. 江苏农业科学, 48(18): 294-299.
	LI H L, HE B Y, YU M T·H L G, et al., 2020. Characteristics of atmospheric particulate concentrations in urban forests in arid areas and its relationship with environmental factors[J]. Jiangsu Agricultural Sciences, 48(18): 294-299.
[26]	粟莉圆, 2021. 火力楠种子园开花动态与繁育系统研究[D]. 南宁: 广西大学: 3-4.
	LI L Y, 2021. Study on the flowering dynamics and breeding system in seed orchard of Michelia macclurei[D]. Nanning: Guangxi University: 3-4.
[27]	李少宁, 刘斌, 鲁笑颖, 等, 2016. 北京常见绿化树种叶表面形态与PM_2.5吸滞能力关系[J]. 环境科学与技术, 39(10): 62-68.
	LI S N, LIU B, LU X Y, et al., 2016. Relationship between leaf surface morphology and PM_2.5 adsorption capacity of common greening tree species in Beijing[J]. Environmental Science & Technology, 39(10): 62-68.
[28]	李新宇, 赵松婷, 李延明, 等, 2014. 北京市不同主干道绿地群落对大气PM_2.5浓度消减作用的影响[J]. 生态环境学报, 23(4): 615-621.
	LI X Y, ZHAO S T, LI Y M, et al., 2014. Subduction effect of urban arteries green space on atmospheric concentration of PM_2.5 in Beijing[J]. Ecology and Environmental Sciences, 23(4): 615-621.
[29]	廖莉团, 苏欣, 李小龙, 等, 2014. 城市绿化植物滞尘效益及滞尘影响因素研究概述[J]. 森林工程, 30(2): 21-24, 28.
	LIAO L T, SU X, LI X L, et al., 2014. Review on the purification effects of urban landscape plants and factors affecting detaining dust[J]. Forest Engineering, 30(2): 21-24, 28.
[30]	刘斌, 鲁绍伟, 李少宁, 等, 2016. 北京大兴6种常见绿化树种吸附PM_2.5能力研究[J]. 环境科学与技术, 39(2): 31-37.
	LIU B, LU S W, LI S N, et al., 2016. Study on adsorption ability of PM_2.5 about six common landscape plants in Daxing District, Beijing[J]. Environmental Science & Technology, 39(2): 31-37.
[31]	刘浩栋, 陈亚静, 李清殿, 等, 2020. 城市道路林对细颗粒物 (PM_2.5) 的阻滞作用解析[J]. 浙江农林大学学报, 37(3): 397-406.
	LIU H D, CHEN Y J, LI Q D, et al., 2020. Analysis of blocking effects of urban roadside forests on PM_2.5[J]. Journal of Zhejiang A & F University, 37(3): 397-406.
[32]	刘旭辉, 2016. 北京地区典型人工林对空气颗粒物浓度的影响[D]. 北京: 北京林业大学:19-20.
	LIU X H, 2016. Influence of plantation ecosystems on atmospheric particles concentration in Beijing region[D]. Beijing: Beijing Forestry University:19-20.
[33]	刘一超, 王萌, 梁琼, 等, 2018. 北京通州不同树种滞纳大气颗粒物的能力[J]. 北京农学院学报, 33(1): 84-88.
	LIU Y C, WANG M, LIANG Q, et al., 2018. Study on the atmospheric particulate matter adsorption capacity of different tree species in Tongzhou District of Beijing[J]. Journal of Beijing University of Agriculture, 33(1): 84-88.
[34]	卢万鸿, 罗建中, 曹加光, 2010. 不同树龄、种源尾叶桉的开花结实情况调查[J]. 桉树科技, 27(2): 39-42.
	LU W H, LUO J Z, CAO J G, 2010. Investigation on florescence and seeding of different provenances and ages of Eucalyptus urophylla[J]. Eucalypt Science & Technology, 27(2): 39-42.
[35]	罗传秀, 苏翔, 杨艺萍, 2017. 广州市孢粉致敏病学研究与预报[R]. 广东省, 中国科学院南海海洋研究所: 1-2.
	LUO C X, SU X, YANG Y P, 2017. Study and prediction of sporopollen allergies in Guangzhou[R]. Institute of Oceanology Chinese Academy of Sciences, Guangdong Province: 1-2.
[36]	鲁绍伟, 蒋燕, 陈波, 等, 2017. 北京城市植被区PM_2.5浓度时空变化及影响因素分析[J]. 环境科学与技术, 40(1): 180-187.
	LU S W, JIANG Y, CHEN B, et al., 2017. Analysis on spatial-temporal variation and influential factors of PM_2.5mass concentration in Beijing’s urban forest[J]. Environmental Science & Technology, 40(1): 180-187.
[37]	潘丽琴, 郝建, 徐建民, 等, 2018. 灰木莲花期物侯观测及生殖构件分布[J]. 林业科学研究, 31(2): 92-97.
	PAN L Q, HAO J, XU J M, et al., 2018. Flowering phenology and reproductive modules distribution of Manglietia glance blune[J]. Forest Research, 31(2): 92-97.
[38]	舒德远, 丁访军, 刘延惠, 等, 2017. 贵阳市城郊常绿落叶阔叶混交林对大气颗粒物的影响[J]. 贵州林业科技, 45(1): 15-21.
	SHU D Y, DING F J, LIU Y H, 2017. Impact of evergreen and deciduous broad-leaved mixed forest on atmospheric particulates in suburb of Guiyang City[J]. Guizhou Forestry Science and Technology, 45(1): 15-21.
[39]	谭超, 郑慧梓, 马艺天, 2022. 绿色发展享誉世界[N]. 南方日报, [2022-07-12]. AA4.
	TAN C, ZHENG H Z, MA Y T, 2022. Green development is world-renowned[N]. Southern Daily, [2022-07-12]. AA4.
[40]	王兵, 张维康, 牛香, 等, 2015. 北京10个常绿树种颗粒物吸附能力研究[J]. 环境科学, 36(2): 408-414.
	WANG B, ZHANG W K, NIU X, et al., 2015. Particulate matter adsorption capacity of 10 evergreen species in Beijing[J]. Environmental Science, 36(2): 408-414.
[41]	王科朴, 张语克, 刘雪华, 2020. 北京城市绿地对大气颗粒物的削减量计算[J]. 环境科学与技术, 43(4): 121-129.
	WANG K P, ZHANG Y K, LIU X H, 2020. Modeled particulate matters removal by urban green lands in Beijing[J]. Environmental Science & Technology, 43(4): 121-129.
[42]	王磊, 黄利斌, 万欣, 等, 2016. 城市森林对大气颗粒物 (尤其PM_2.5) 调控作用研究进展[J]. 南京林业大学学报(自然科学版), 40(5): 148-154.
	WANG L, HUANG L B, WAN X, et al., 2016. Progress on the regulating effects of urban forest vegetation on atmospheric particulate matter (especially PM_2.5)[J]. Journal of Nanjing Forestry University (Natural Sciences Edition), 40(5): 148-154.
[43]	王萌, 刘一超, 梁琼, 等, 2018. 北京城市森林公园不同树种吸附大气颗粒物能力[J]. 北京农学院学报, 33(1): 79-83.
	WANG M, LIU Y C, LIANG Q, et al., 2018. Study on the atmospheric particulate matters adsorption capacity of different tree species in urban forest park of Beijing[J]. Journal of Beijing University of Agriculture, 33(1): 79-83.
[44]	王忠, 欧阳婵娟, 罗燕燕, 等, 2007. 乡土植物在广州城市园林绿化中的应用[J]. 亚热带植物科学, 36(4): 33-37.
	WANG Z, OUYANG C J, LUO Y Y, et al., 2007. Application of indigenous plants to urban landscap in Guangzhou[J]. Subtropical Plant Scienc, 36(4): 33-37.
[45]	王轶浩, 凯旋, 谢双喜, 2016. 重庆铁山坪森林植被调控下的大气PM_2.5和PM₁₀特征[J]. 四川林业科技, 37(6): 54-58.
	WANG Y H, KAI X, XIE S X, 2016. Characteristics of atmospheric PM_2.5 and PM₁₀ regulated by forest vegetation in the Tieshanping forest park of Chongqing[J]. Journal of Sichuan Forestry Science and Technology, 37(6): 54-58.
[46]	肖小军, 谢雄杰, 康敏雄, 等, 2011. 深圳市春季气传致敏花粉的调查[J]. 免疫学杂志, 27(10): 837-839, 844.
	XIAO X J, XIE X J, KANG M X, et al., 2011. Investigation on airborne pollen in spring of Shenzhen[J]. Immunological Journal, 27(10): 837-839, 844.
[47]	杨期和, 黄楚琪, 王燕华, 2018. 粤东山区山茶科植物资源及其开发利用初探[J]. 中国野生植物资源, 37(3): 56-63.
	YANG Q H, HUANG C Q, WANG Y H, 2018. A preliminary study on the exploitation and utilization of theaceae plant resources in the mountainous area of eastern Guangdong[J]. Chinese Wild Plant Resources, 37(3): 56-63.
[48]	杨伟儿, 张乔松, 周先武, 2006. 广州城市绿地生物多样性的现状与展望[J]. 广东园林, 28(2): 47-51, 55.
	YANG W E, ZHANG Q S, ZHOU X W, 2006. Gurrent status and prospects of iodiversity in Guangzhou urban green space[J]. Guangdong Landscape Architecture, 28(2): 47-51, 55.
[49]	喻明美, 谢正生, 2011. 广州市白云山五种森林类型的土壤渗透性研究[J]. 水土保持研究, 18(1): 153-156.
	YU M M, XIE Z S, 2011. Study on soil permeability capability of five forest types in Baiyunshan scenic spot of Gangzhou[J]. Research of Soil and Water Conservation, 18(1): 153-156.
[50]	张刘东, 郭建曜, 万家隆, 等, 2021. 泰山景区不同林型空气颗粒物浓度研究[J]. 中国农学通报, 37(19): 100-105. DOI
	ZHANG L D, GUO J Y, WAN J L, et al., 2021. Study on ambient particulate matter concentration of different forest types in Mountain Tai Scenic Area[J]. Chinese Agricultural Science Bulletin, 37(19): 100-105. DOI
[51]	张雅慧, 廖景平, 张容妹, 等, 2020. 华南植物园藤本植物专类园规划设计[J]. 中国园林, 36(10): 92-97.
	ZHANG Y H, LIAO J P, ZHANG R M, et al., 2020. The planning and design of the specialized gardenfor vine plants in South China Botanical Garden[J]. Chinese Landscape Architecture, 36(10): 92-97.
[52]	张志国, 2016. 森林城市群让广东更美丽[J]. 绿色中国 (23): 18-23.
	ZHANG Z G, 2016. Forest city group make more beautiful in Guangdong[J]. Green China (23): 18-23.
[53]	赵云阁, 鲁笑颖, 刘斌, 等, 2016. 夏季绿化树种滞留PM_2.5与叶片微形态特征研究[J]. 水土保持研究, 23(6): 52-58.
	ZHAO Y G, LU X Y, LIU B, et al., 2016. Study on four kinds of greening tree retention PM_2.5 and leaf surface morphology during summer in Beijing, China[J]. Research of Soil and Water Conservation, 23(6): 52-58.
[54]	郑铭浩, 2017. 重庆主城区常见树种及植物群落对空气颗粒物的调控作用研究[D]. 重庆: 西南大学:57-61.
	ZHENG M H, 2017. Study on the regulation of common tree species and plant communities on atmospheric particle in urban areas of Chongqing[D]. Chongqing: Master Thesis of Southwest University:57-61.
[55]	朱书银, 2019. 新乡市主城区大气颗粒物的变化特征及来源解析[D]. 新乡: 河南师范大学: 1-2.
	ZHU S Y, 2019. Variation characteristics and source apportionment of atmosphere particul atematterin the main urban area of Xinxiang[D]. Xinxiang: Henan Normal University: 1-2.
[56]	邹杰, 2011. 湿地松种子园花粉散发特性研究[D]. 武汉: 华中农业大学: 1-2.
	ZOU J, 2011. Studies on pollen dispersal characteristic in seed orchard of Pinus elliottii[D]. Wuhan: Huazhong Agricultural University: 1-2.

公园名称	样地	林内外	经度	纬度	距离污染源的最近距离/m	林内外监测点的距离/m	林分类型
华南国家植物园	a1	林内	113.3667	23.1835	229.16	208.57	火力楠-灰木莲 Michelia macclurel-Manglietia glauca
	a2	林外	113.3647	23.1831	363.09	208.57	火力楠-灰木莲 Michelia macclurel-Manglietia glauca
	b1	林内	113.3587	23.1871	229.09	31.72	白千层 Melaleuca leucadendron L.
	b2	林外	113.3584	23.1871	212.45	31.72	白千层 Melaleuca leucadendron L.
白云山风景区	c1	林内	113.3055	23.1884	1159.45	139.48	湿地松-山油柑-柯 Pinus elliottii-Acronychia pedunculata (L.) Miq.-Lithocarpus glaber (Thunb.) Nakai
白云山风景区	c2	林外	113.3041	23.1883	1276.07	139.48
华南国家植物园	d1	林内	113.3604	23.1800	518.70	176.70	尾叶桉 Eucalyptus urophylla S.T. Blake
华南国家植物园	d2	林外	113.3621	23.1805	416.51	176.70	尾叶桉 Eucalyptus urophylla S.T. Blake
白云山风景区	e1	林内	113.2985	23.1844	1711.20	99.06	锥-木荷 Schima superba Gardn. et Champ.-Castanopsis chinensis (Sprengel) Hance
白云山风景区	e2	林外	113.2985	23.1835	1696.63	99.06

公园名称	样地	林内外	经度	纬度	距离污染源的最近距离/m	林内外监测点的距离/m	林分类型
华南国家植物园	a1	林内	113.3667	23.1835	229.16	208.57	火力楠-灰木莲 Michelia macclurel-Manglietia glauca
	a2	林外	113.3647	23.1831	363.09	208.57	火力楠-灰木莲 Michelia macclurel-Manglietia glauca
	b1	林内	113.3587	23.1871	229.09	31.72	白千层 Melaleuca leucadendron L.
	b2	林外	113.3584	23.1871	212.45	31.72	白千层 Melaleuca leucadendron L.
白云山风景区	c1	林内	113.3055	23.1884	1159.45	139.48	湿地松-山油柑-柯 Pinus elliottii-Acronychia pedunculata (L.) Miq.-Lithocarpus glaber (Thunb.) Nakai
白云山风景区	c2	林外	113.3041	23.1883	1276.07	139.48
华南国家植物园	d1	林内	113.3604	23.1800	518.70	176.70	尾叶桉 Eucalyptus urophylla S.T. Blake
华南国家植物园	d2	林外	113.3621	23.1805	416.51	176.70	尾叶桉 Eucalyptus urophylla S.T. Blake
白云山风景区	e1	林内	113.2985	23.1844	1711.20	99.06	锥-木荷 Schima superba Gardn. et Champ.-Castanopsis chinensis (Sprengel) Hance
白云山风景区	e2	林外	113.2985	23.1835	1696.63	99.06

大气颗粒物削减率/质量浓度	颗粒物类型	温度	相对湿度	风速
大气颗粒物削减率/ %	TSP	0.08	-0.12	-0.19^**
	PM₁₀	-0.01	0.03	-0.31^**
	PM_2.5	0.15^**	-0.11	-0.26^**
	PM_1.0	0.21^**	-0.10	-0.23^**
林内大气颗粒物质量浓度/ (μg·m^-3)	TSP	-0.36^**	0.56^**	-0.22^**
	PM₁₀	-0.35^**	0.60^**	-0.22^**
	PM_2.5	-0.36^**	0.63^**	-0.24^**
	PM_1.0	-0.30^**	0.54^**	-0.25^**
林外大气颗粒物质量浓度/ (μg·m^-3)	TSP	-0.38^**	0.58^**	-0.29^**
	PM₁₀	-0.39^**	0.65^**	-0.29^**
	PM_2.5	-0.36^**	0.65^**	-0.27^**
	PM_1.0	-0.30^**	0.57^**	-0.28^**

大气颗粒物削减率/质量浓度	颗粒物类型	温度	相对湿度	风速
大气颗粒物削减率/ %	TSP	0.08	-0.12	-0.19^**
	PM₁₀	-0.01	0.03	-0.31^**
	PM_2.5	0.15^**	-0.11	-0.26^**
	PM_1.0	0.21^**	-0.10	-0.23^**
林内大气颗粒物质量浓度/ (μg·m^-3)	TSP	-0.36^**	0.56^**	-0.22^**
	PM₁₀	-0.35^**	0.60^**	-0.22^**
	PM_2.5	-0.36^**	0.63^**	-0.24^**
	PM_1.0	-0.30^**	0.54^**	-0.25^**
林外大气颗粒物质量浓度/ (μg·m^-3)	TSP	-0.38^**	0.58^**	-0.29^**
	PM₁₀	-0.39^**	0.65^**	-0.29^**
	PM_2.5	-0.36^**	0.65^**	-0.27^**
	PM_1.0	-0.30^**	0.57^**	-0.28^**

颗粒物类型	林外大气颗粒物质量浓度/(μg·m^-3)
颗粒物类型	TSP	PM₁₀	PM_2.5	PM_1.0
TSP	0.04	-0.02	-0.10	-0.09
PM₁₀	0.00	0.01	-0.02	-0.00
PM_2.5	-0.25^**	-0.21^**	-0.22^**	-0.21^**
PM_1.0	-0.29^**	-0.23^**	-0.22^**	-0.21^**

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

广州典型城市林地对大气颗粒物的削减效应及影响因素

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尺度	颗粒物类型	冠幅1	冠幅2	平均树高	优势种密度	叶面积指数
半小时 (n=205)	TSP	-0.14^*	-0.12	0.03	0.05	0.22^**
	PM₁₀	-0.31^**	-0.30^**	-0.05	0.02	0.30^**
	PM_2.5	-0.32^**	-0.35^**	-0.11	-0.03	0.27^**
	PM_1.0	-0.31^**	-0.34^**	-0.13	-0.03	0.19^**
日 (n=14)	TSP	-0.03	0.06	-0.07	-0.07	0.15
	PM₁₀	-0.21	-0.18	-0.21	-0.13	0.27
	PM_2.5	-0.36	-0.44	-0.24	-0.10	0.25
	PM_1.0	-0.50	-0.58^*	-0.16	0.02	0.31
林地 (n=5)	TSP	0.03	0.17	-0.09	0.03	0.26
	PM₁₀	-0.20	-0.06	-0.20	0.09	014
	PM_2.5	-0.31	-0.58	-0.49	-0.26	0.09
	PM_1.0	-0.43	-0.73	-0.54	-0.20	0.03

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