Relationship between air pollution purification and forest belt width of the Shanghai green belt in the summer season

doi:10.3969/j.issn.1000-5641.2021.03.013

Abstract

Abstract:

In this study, ground-level air pollutants (i.e., particulate matter (PM), NO₂, and CO) were monitored at two transects of an urban-road-green-belt of Shanghai for one month during the summer season. Four monitoring sites at 100m intervals were set along each transect from the road to the inside. The air pollution was evaluated for each site based on China’s national standard, and the variation in air pollution purification ability (i.e., removal percentage) was compared among sites with different distances to the road. The effects of meteorological condition and pollution background on maximum removal percentage of each air pollutant were evaluated by multiple regression analysis. The results showed that the green belt greatly contributed to reducing PM_2.5, PM₁₀, and NO₂; however, the green belt also produced a cumulative effect on CO generation within its boundaries. The green belt had the greatest air pollution purification performance at sites with 300m distance to the road for most pollutants in both transects. The maximum removal percentages of PM_2.5 and PM₁₀ were correlated to air humidity difference and air temperature difference between outer and inner of forests mostly, while the maximum removal percentages of NO₂ were correlated to the pollution background and maximum removal percentages of CO were correlated to air temperature difference. The results can provide a theoretical foundation for forest transform and arrangement aimed at air pollution purification in the green belt.

Key words: Shanghai green belt, air pollution, forest belt width, urban forest, ecological benefits

CLC Number:

X835

Xiaoling WANG, Kun SONG, Ying LE, Jing CHEN, Hao JIANG, Yongjia ZHANG, Heyi GONG, Zifei WANG, Yi DING, Tianhui SHI, Liangjun DA. Relationship between air pollution purification and forest belt width of the Shanghai green belt in the summer season[J]. Journal of East China Normal University(Natural Science), 2021, 2021(3): 128-137.

Figures/Tables 6

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References 38

1	CHANG Y S, ARNDT R L, CALORI G, et al. Air quality impacts as a result of changes in energy use in China’s Jiangsu Province. Atmos Environ, 1998, 32 (8): 1383- 1395. doi: 10.1016/S1352-2310(97)00134-9
2	SUN J, ZHANG J H, WANG Y, et al. Escape or stay? Effects of haze pollution on domestic travel: Comparative analysis of different regions in China. Sci Total Environ, 2019, 690, 151- 157. doi: 10.1016/j.scitotenv.2019.06.415
3	LIU Z, HU B, JI D, et al. Characteristics of fine particle explosive growth events in Beijing, China: Seasonal variation, chemical evolution pattern and formation mechanism. Sci Total Environ, 2019, 687, 1073- 1086. doi: 10.1016/j.scitotenv.2019.06.068
4	JIM C Y, CHEN W Y. Assessing the ecosystem service of air pollutant removal by urban trees in Guangzhou (China). J Environ Manage, 2008, 88 (4): 665- 676. doi: 10.1016/j.jenvman.2007.03.035
5	GONG P, LIANG S, CARLTON E J, et al. Urbanisation and health in China. The Lancet, 2012, 379 (9818): 843- 852. doi: 10.1016/S0140-6736(11)61878-3
6	黄焰城, 章君果, 沈沉沉, 等. 宁波镇海区生态隔离林带净化大气的生态效益. 华东师范大学学报(自然科学版), 2009, (2): 1- 10. doi: 10.3969/j.issn.1000-5641.2009.02.001
7	王晓磊, 王成. 城市森林调控空气颗粒物功能研究进展. 生态学报, 2014, 34 (8): 1910- 1921.
8	殷杉, 蔡静萍, 陈丽萍, 等. 交通绿化带植物配置对空气颗粒物的净化效益. 生态学报, 2007, (11): 4590- 4595. doi: 10.3321/j.issn:1000-0933.2007.11.026
9	NOWAK D J, CRANE D E, STEVENS J C. Air pollution removal by urban trees and shrubs in the United States. Urban For Urban Gree, 2006, 4 (3): 115- 123.
10	NOWAK D J, HIRABAYASHI S, BODINE A, et al. Tree and forest effects on air quality and human health in the United States. Environ Pollut, 2014, 193, 119- 129. doi: 10.1016/j.envpol.2014.05.028
11	CHEN L X, LIU C M, ZOU R, et al. Experimental examination of effectiveness of vegetation as bio-filter of particulate matters in the urban environment. Environ Pollut, 2016, 208, 198- 208. doi: 10.1016/j.envpol.2015.09.006
12	张凯旋, 张建华. 上海环城林带保健功能评价及其机制. 生态学报, 2013, 33 (13): 4189- 4198.
13	范昕婷, 郭雪艳, 方燕辉, 等. 上海市环城绿带生态系统服务价值评估. 城市环境与城市生态, 2013, 26 (5): 1- 5.
14	沈沉沉. 上海市环城绿带生态系统服务功能评价及其价值评估 [D]. 上海: 华东师范大学, 2011.
15	ROORDA-KNAPE M C, JANSSEN N A H, DE HARTOG J J, et al. Air pollution from traffic in city districts near major motorways. Atmos Environ, 1998, 32 (11): 1921- 1930. doi: 10.1016/S1352-2310(97)00496-2
16	KODAMA Y, ARASHIDANI K, TOKUI N, et al. Environmental NO₂ concentration and exposure in daily life along main roads in Tokyo . Environ Res, 2002, 89 (3): 236- 244. doi: 10.1006/enrs.2002.4350
17	TRUSCOTT A M, PALMER S C F, MCGOWAN G M, et al. Vegetation composition of roadside verges in Scotland: The effects of nitrogen deposition, disturbance and management. Environ Pollut, 2005, 136 (1): 109- 118. doi: 10.1016/j.envpol.2004.12.009
18	YIN S, SHEN Z, ZHOU P, et al. Quantifying air pollution attenuation within urban parks: An experimental approach in Shanghai, China. Environ Pollut, 2011, 159 (8): 2155- 63.
19	刘浩栋. 城市道路林内大气颗粒物的时空变化特征——以泰安市为例 [D]. 山东泰安: 山东农业大学, 2017.
20	BRANTLEY H L, HAGLER G S W, J. DESHMUKH P, et al. Field assessment of the effects of roadside vegetation on near-road black carbon and particulate matter. Sci Total Environ, 2014, 468-469, 120- 129. doi: 10.1016/j.scitotenv.2013.08.001
21	YLI-PELKONEN V, VIIPPOLA V, KOTZE J, et al. Greenbelts do not reduce NO₂ concentrations in near-road environments . Urban Climate, 2017, 21, 306- 317. doi: 10.1016/j.uclim.2017.08.005
22	张凯旋. 上海环城林带群落生态学与生态效益及景观美学评价研究 [D]. 上海: 华东师范大学, 2010.
23	SMSB (Shanghai Municipal Statistics Bureau). Shanghai Statistical Yearbook 2017 [M]. 1st ed. Beijing: China Statistics Press, 2018.
24	达良俊, 杨同辉, 宋永昌. 上海城市生态分区与城市森林布局研究. 林业科学, 2004, 40 (4): 84- 88. doi: 10.3321/j.issn:1001-7488.2004.04.015
25	孙诗雨. 上海环城绿带百米林带植物群落游憩适宜度评价研究 [D]. 上海: 上海交通大学, 2018.
26	PARSA V A, SALEHI E, YAVARI A R, et al. Analyzing temporal changes in urban forest structure and the effect on air quality improvement. Sustainable Cities and Society, 2019, 48, 101548. doi: 10.1016/j.scs.2019.101548
27	国家环境保护局, 国家技术监督局. GB3095—2012中华人民共和国国家标准-环境空气质量标准 [S]. 北京: 中国环境科学出版社, 2012.
28	徐晓男. 林带对PM_2.5的吸附效应研究——以诸城市不同林带为例 [D]. 山东泰安: 山东农业大学, 2015.
29	吴海萍. 上海浦东道路绿地群落结构、生态功能及调整优化研究 [D]. 上海: 华东师范大学, 2007.
30	魏欣, 寇英卫, 柏育材. 上海越江隧道机动车尾气污染物排放特征. 上海船舶运输科学研究所学报, 2015, 38 (3): 11- 14. doi: 10.3969/j.issn.1674-5949.2015.03.003
31	张晗宇, 程水源, 姚森, 等. 2016年10 ~ 11月期间北京市大气颗粒物污染特征与传输规律. 环境科学, 2019, 40 (5): 1999- 2009.
32	刘小真, 任羽峰, 刘忠马, 等. 南昌市大气颗粒物污染特征及PM_2.5来源解析 . 环境科学研究, 2019, 32 (9): 1546- 1555.
33	汪嘉熙. 大气污染与植物的相互关系. 生物学通报, 1985, (6): 1- 2.
34	YLI-PELKONEN V, SETÄLÄ H, VIIPPOLA V. Urban forests near roads do not reduce gaseous air pollutant concentrations but have an impact on particles levels. Landscape Urban Plann, 2017, 158, 39- 47. doi: 10.1016/j.landurbplan.2016.09.014
35	JIAO M, ZHOU W, ZENG Z, et al. Patch size of trees affects its cooling effectiveness: A perspective from shading and transpiration processes. Agricultural and Forest Meteorology, 2017, 247, 293- 299. doi: 10.1016/j.agrformet.2017.08.013
36	赵帅. 成都市活水公园内植物群落在不同天气条件下对PM_2.5和PM₁₀浓度变化的影响研究 [D]. 成都: 四川农业大学, 2018.
37	李素莉. 北京典型配置城市森林对PM_2.5影响研究 [D]. 北京: 北京林业大学, 2015.
38	王晓磊. 道路防护林内大气颗粒物时空变化规律研究 [D]. 北京: 中国林业科学研究院, 2014.

林带宽度	PM_2.5				PM₁₀				NO₂				CO
	均值/%		标准差		均值/%		标准差		均值/%		标准差		均值/%		标准差
	盛宅段	康桥段	盛宅段	康桥段	盛宅段	康桥段	盛宅段	康桥段	盛宅段	康桥段	盛宅段	康桥段	盛宅段	康桥段	盛宅段	康桥段
100 m	6.82	–10.21	0.15	0.15	2.52	–14.54	0.17	0.19	13.57	–11.06	0.28	0.38	–72.97	–14.81	0.31	0.18
200 m	6.65	3.25	0.11	0.15	7.05	3.39	0.12	0.17	11.64	31.05	0.19	0.37	–116.36	–19.86	0.28	0.35
300 m	9.69	19.12	0.14	0.23	7.22	17.67	0.18	0.26	29.82	24.53	0.26	0.25	23.53	–6.49	0.42	0.24
400 m	–5.88	–1.35	0.14	0.13	–1.55	3.12	0.15	0.15	1.20	–0.78	0.30	0.30	–14.3	–15.79	0.23	0.19

模型	序号	自变量	系数	标准误差	t	Sig.	相对重要性	调整R²
PM_2.5为因变量	1	污染物浓度	–0.2431	0.156	–1.556	0.128	0.088	0.464
	2	温度差	–59.503	10.518	–5.657	< 0.001***	0.443
	3	湿度差	–13.275	2.292	–5.791	< 0.001***	0.469
PM₁₀为因变量	1	污染物浓度	–0.171	0.128	–1.335	0.19	0.056	0.501
	2	温度差	–65.908	10.766	–6.122	< 0.001***	0.445
	3	湿度差	–14.902	2.348	–6.346	< 0.001***	0.499
NO₂为因变量	1	污染物浓度	86.245	30.504	2.827	0.0075**	0.357	0.437
	2	温度差	–13.061	4.929	–2.650	0.012*	0.411
	3	湿度差	–1.672	1.085	–1.541	0.132	0.231
CO为因变量	1	温度差	122.740	48.490	2.531	0.016*	0.662	0.125
CO为因变量	2	湿度差	20.890	10.630	1.966	0.057	0.338	0.125

[1]	HAN Yu-jie, SUN Wen, ZHANG Wen-wen. Evaluation of ecosystem services for urban forests in Shanghai based on a distribution measurement methodology [J]. Journal of East China Normal University(Natural Sc, 2019, 2019(2): 147-155.
[2]	ZHANG Kai-xuan, CHE Sheng-quan, MA Shao-chu,WANG Rui, DA Liang-jun. Diversity, spatial pattern and dynamics of vegetation under urbanization in Shanghai (Ⅵ): Community diversity and its structural characteristics of Shanghai Green Belt [J]. Journal of East China Normal University(Natural Sc, 2011, 2011(4): 1-14,74.
[3]	YIN Jun-guang;PENG Yuan;ZHANG Jun-guo;DA Liang-jun;. Study on ecological benefits of urban near-natural forests (Chinese) [J]. Journal of East China Normal University(Natural Sc, 2009, 2009(5): 63-74.
[4]	HUANG Yan-cheng;ZHANG Jun-guo;SHEN Chen-chen;XU Wei;XIA Ti-yuan;DA Liang-jun;ZHOU Na . Study on ecological benefits about air purification of ecologicalforest belts in Zhenhai district, Ningbo（Chinese） [J]. Journal of East China Normal University(Natural Sc, 2009, 2009(2): 1-10.
[5]	LIU Na-na;LI Lin;DA Liang-jun. Evaluation System of Ecologica1 Benefits of Waterscape and Its Appplication in Urban Residential Areas(Chinese) [J]. Journal of East China Normal University(Natural Sc, 2006, 2006(6): 75-83.