Spatio-temporal Distribution Characteristics of PM2.5 and Air Quality Evaluation in Urban Street Canyons: Take Changhuai Street in Hefei as An Example

doi:10.16258/j.cnki.1674-5906.2021.11.006

Ecology and Environment ›› 2021, Vol. 30 ›› Issue (11): 2157-2164.DOI: 10.16258/j.cnki.1674-5906.2021.11.006

• Research Articles • Previous Articles Next Articles

Spatio-temporal Distribution Characteristics of PM_2.5 and Air Quality Evaluation in Urban Street Canyons: Take Changhuai Street in Hefei as An Example

WANG Wei¹^,²(), CHENG Xinyue¹, HU Chun¹^,², XIA Sihan¹, WANG Tian¹

1. School of Architecture and Urban Planning, Anhui Jianzhu University, Hefei 230022, China
2. Key Laboratory of Built Environment and Health, Anhui Jianzhu University, Hefei 230022, China

Received:2021-06-11 Online:2021-11-18 Published:2021-12-29

城市街道峡谷PM_2.5时空分布特征与空气质量评价——以合肥市长淮街道为例

王薇¹^,²(), 程歆玥¹, 胡春¹^,², 夏斯涵¹, 王甜¹

1.安徽建筑大学建筑与规划学院,安徽合肥 230022
2.安徽建筑大学建成环境与健康重点实验室,安徽合肥 230022

作者简介:王薇（1975年生）,女,教授,博士,研究方向为建筑技术和人居环境。E-mail: vivi.gan@126.com
基金资助:
国家自然科学基金项目(51778001);国家重点研发计划(2017YFC0702503);安徽省教育厅高校优秀拔尖人才培育资助项目(gxbJZD23)

Abstract

Abstract:

The air pollution represented by PM_2.5 has a great impact on the life of urban residents. Street canyon is an important part of the city and one of the main places where urban residents live. In this study, PM_2.5 was taken as the research object. From January 22 to January 24, 2021, seven fixed monitoring stations were set up in the street canyon of Changhuai Street, Yaohai District, Hefei City, and the pollution level of PM_2.5 in the street canyon of Hefei City in winter and its influencing factors were analyzed with reference to the national control point of Sanli Street nearby. The results show that, (1) the average daily mass concentration of PM_2.5 in street canyons presents a “W”-shaped variation. Non-essential commuters in street canyons should avoid traveling at noon peak on working days, and can choose to travel between 15:00 and 16:00. (2) The trend of PM_2.5 concentration in different street canyons was: road intersection>roadside>community park green space>general street canyons. The larger the wind speed is, the farther it is from the emission pollution source and the closer it is to the greening plants, the lower the mass concentration of PM_2.5. Park green space, wide street canyon, reducing the height of windward buildings and increasing street width can all reduce the PM_2.5 concentration in street canyon. The leeward side of the rising street canyon is easy to cause the accumulation of PM_2.5 with high mass concentration. (3) In winter, the air quality level of PM_2.5 is moderate pollution, and the air quality level is Grade 4. The contribution of humidity to PM_2.5 concentration in street canyons is greater than that of temperature, and the contribution of humidity and temperature to PM_2.5 concentration in street canyons is 80.5% and 54.7%, respectively.

Key words: street canyon, PM_2.5, temporal and spatial distribution, air quality evaluation, temperature and humidity, wind speed, traffic flow

摘要：

以PM_2.5为代表的空气污染对城市居民的生活产生了巨大的影响。街道峡谷是城市的重要构成部分,是城市居民生活的主要场所之一。以PM_2.5为研究对象,于2021年1月22—24日在合肥市瑶海区长淮街道的街道峡谷设立7个固定式监测点,并以附近的三里街国控点为参照,分析冬季合肥市街道峡谷的PM_2.5污染水平及其影响因素。研究表明,（1）街道峡谷内PM_2.5日均质量浓度呈现“W”型变化特征。在街道峡谷非必要通勤市民,应避免在工作日午高峰出行,可以选择在15:00—16:00出行。（2）不同街道峡谷内PM_2.5质量浓度大小趋势为：道路交叉口>道路旁>小区公园绿地>一般街道峡谷。风速越大,距离排放污染源越远,距离绿化植物越近,PM_2.5质量浓度越低。公园绿地、宽阔型街道峡谷、降低迎风面建筑高度和增加街道宽度都能降低街道峡谷内部的PM_2.5质量浓度。上升型街道峡谷的背风侧易造成高质量浓度PM_2.5累积。（3）对合肥市长淮街道冬季而言,PM_2.5的空气质量水平为中度污染,空气质量级别为四级。湿度对街道峡谷的PM_2.5质量浓度贡献度比温度更大,湿度和温度对街道峡谷的PM_2.5质量浓度贡献度分别为80.5%和54.7%。

关键词: 街道峡谷, PM_2.5, 时空分布, 空气质量评价, 温湿度, 风速, 车流量

CLC Number:

WANG Wei, CHENG Xinyue, HU Chun, XIA Sihan, WANG Tian. Spatio-temporal Distribution Characteristics of PM_2.5 and Air Quality Evaluation in Urban Street Canyons: Take Changhuai Street in Hefei as An Example[J]. Ecology and Environment, 2021, 30(11): 2157-2164.

王薇, 程歆玥, 胡春, 夏斯涵, 王甜. 城市街道峡谷PM_2.5时空分布特征与空气质量评价——以合肥市长淮街道为例[J]. 生态环境学报, 2021, 30(11): 2157-2164.

Figures/Tables 10

References 5

[1]	HU C B, ZHANG F, GUO F Y, et al., 2020. Classification and mapping of urban canyon geometry using Google Street View images and deep multitask learning[J]. Building and Environment, DOI: 10.1016/j.buildenv.2019.106424. DOI
[2]	NICHOLSON S E, 1975. A pollution model for street-level air[J]. Atmospheric Environment, 9(1): 19-31.
[3]	WEI Z H, PENG J X, MA X W, et al., 2021. Toward PM_2.5 Distribution Patterns Inside Symmetric and Asymmetric Street Canyons: Experimental Study[J]. Journal of Environmental Engineering, DOI: 10.1061/(ASCE)EE.1943-7870.0001878. DOI
[4]	柴晋鹏, 陈学刚, 赵直, 2021. 基于移动监测的城市街谷交通相关污染物浓度时空变化研究[J]. 地球与环境, 49(4): 389-399.
	CHAI J P, CHEN X G, ZHAO Z, 2021. Study on the temporal and spatial variation of traffic-related pollutants concentration in urban streets and valleys based on mobile monitoring[J]. Earth and Environment, 49(4): 389-399.
[5]	邓寄豫, 郑炘, 2017. 街区层峡几何形态与微气候的关联性研究[J]. 建筑与文化, 14(5): 212-213.
	DENG J Y, ZHENG K, 2017. Study on the relationship between the geometry of the block gorge and microclimate[J]. Architecture and Culture, 14(5): 212-213.
[6]	葛晓燕, 2018. 城市典型街谷道路中污染物扩散特征模拟[D]. 西安: 西安建筑科技大学: 29-56.
	GE X Y, 2018. Simulation of pollutant diffusion characteristics in typical urban streets and valleys[D]. Xi’an: Xi’an University of Architecture and Technology:29-56.
[7]	郭云, 蒋玉丹, 黄炳昭, 等, 2021. 我国大气PM_2.5及O₃导致健康效益现状分析及未来10年预测[J]. 环境科学研究, 34(4): 1023-1032.
	GUO Y, JIANG Y, HUANG B Z, et al., 2021. Analysis of the current health benefits of my country’s atmospheric PM_2.5 and O₃ and its prediction in the next 10 years[J]. Environmental Science Research, 34(4): 1023-1032.
[8]	合肥市生态环境局, 2021. 2020年合肥市环境状况公报[N/OL]. (2021-06-04) [2021-06-04]. http://sthjj.hefei.gov.cn/hbzx/gsgg/18085969.html .
	Hefei Municipal Bureau of Ecology and Environment, 2020. Bulletin on Environmental Status of Hefei City from 2021 to 2020 [N/OL]. (2021-06-04) [2021-06-04]. http://sthjj.hefei.gov.cn/hbzx/gsgg/18085969.html .
[9]	黄慧芬, 2019. 合肥市城市空间形态演变多尺度研究( 1949- 2015 年)[D]. 合肥: 合肥工业大学: 21-54.
	HUANG H F, 2019. Multi-scale study on the evolution of urban spatial form in Hefei ( 1949-2015)[D]. Hefei: Hefei University of Technology: 21-54.
[10]	李小东, 张玉鹏, 李德, 2018. 合肥瑶海区旧城更新改造规划路径探索[J]. 规划师, 34(S1): 44-49.
	LI X D, ZHANG Y P, LI D, 2018. Exploration on the planning path of old city renewal and reconstruction in Yaohai District of Hefei[J]. Planner, 34(S1): 44-49.
[11]	邱巧玲, 王凌, 2007. 基于街道峡谷污染机理的城市街道几何结构规划研究[J]. 城市发展研究 (4): 78-82.
	QIU Q L, WANG L, 2007. Research on Urban Street Geometric Structure Planning Based on the Pollution Mechanism of Street Canyon[J]. Urban Development Research (4): 78-82.
[12]	2018. 关于发布《环境空气质量标准》(GB 3095-2012)修改单的公告
	[[2021-06-04]
	and2018. Announcement on Issuing the Revision Sheet of Ambient Air Quality Standard (GB 3095-2012)
	[[2021-06-04]
[13]	王宝民, 柯咏东, 桑建国, 2005. 城市街谷大气环境研究进展[J]. 北京大学学报(自然科学版), 41(1): 146-153.
	WANG B M, KE Y D, SANG J G, 2005. Research progress of atmospheric environment in urban street canyons[J]. Journal of Peking University (Natural Science Edition), 41(1): 146-153.
[14]	王飞, 吴开亚, 王慧慧, 等, 2014. 合肥市PM_2.5与用地类型特征比较及建设性方案研究[J]. 环境科学与管理, 39(10): 73-79.
	WANG F, WU K Y, WANG H H, et al., 2014. Comparison of PM_2.5 and land use type characteristics in Hefei City and study on constructive plans[J]. Environmental Science and Management, 39(10): 73-79.
[15]	王薇, 张之秋, 2014. 城市住区空气负离子浓度时空变化及空气质量评价--以合肥市为例[J]. 生态环境学报, 23(11): 1783-1791.
	WANG W, ZHANG Z Q, 2014. Spatio-temporal Change of Negative Air Ion Concentration of Urban Residential Area and Air Quality Assessment--Case Study of Hefei City[J]. Journal of Ecological Environment, 23(11): 1783-1791.
	闫秀婧, 2009. 青岛市森林与湿地负离子水平时空分布研究[D]. 北京: 北京林业大学: 13-14.
	aYAN X J, 2009. Research on the Spatial and Temporal Distribution of Anion Levels in Forests and Wetlands in Qingdao City[D]. Beijing: Beijing Forestry University: 13-14.
[1]	于洋, 刘晓宇, 田达睿, 等, 2020. 街道峡谷几何形态规划要素对太阳能潜力的影响研究[J]. 工业建筑, 50(7): 137-142.
	YU Y, LIU X Y, TIAN D R, et al., 2020. Research on the influence of street canyon geometry planning elements on solar energy potential[J]. Industrial Construction, 50(7): 137-142.
[2]	臧振峰, 张凤英, 李永华, 等, 2021. 我国主要粮产区PM_2.5、PM₁₀时空分布特征及影响因素--以河南省为例[J]. 自然资源学报, 36(5): 1163-1175.
	ZANG Z F, ZHANG F Y, LI Y H, et al., 2021. Spatio-temporal distribution and affecting factors of PM_2.5 and PM₁₀ in major grain producing areas in China: A case study of Henan province[J]. Journal of Natural Resources, 36(5): 1163-1175. DOI URL
[3]	张云伟, 王晴茹, 陈嘉, 等, 2016. 城市街谷内PM_2.5浓度时空变化及影响因素分析[J]. 中国环境科学, 36(10): 2944-2949.
	ZHANG Y W, WANG Q R, CHEN J, et al., 2016. Analysis of Temporal and Spatial Changes of PM_2.5 Concentration in Urban Streets and Valleys and Influencing Factors[J]. China Environmental Science, 36(10): 2944-2949.
[4]	中央人民政府, 2020. 政府工作报告-2020年5月22日在第十三届全国人民代表大会第三次会议上[N/OL]. (2020-05-29) [2020-05-29]. http://www.gov.cn/premier/2020-05/29/content_5516072.htm .
	Central People’s Government, 2020. government work report-at the third session of the 13th national people’s congress on May 22, 2020 [N/OL]. (2020-05-29) [2020-05-29]. http://www.gov.cn/premier/2020-05/29/content_5516072.htm .
[5]	周洪昌, 杨佩昆, 高延令, 1994. 城市街道汽车排放物扩散过程的风洞试验[J]. 同济大学学报 (自然科学版), 39(3): 306-311.
	ZHOU H C, YANG P K, GAO Y L, 1994. Wind tunnel test on the diffusion process of automobile emissions from urban streets[J]. Journal of Tongji University (Natural Science Edition), 39(3): 306-311.

空气质量指数 Air quality index	PM_2.5日均值 Daily mean value of PM_2.5/(μg∙m^-3)
0	0
50	35
100	75
150	115
200	150
300	250
400	350
500	500

空气质量指数 Air quality index	PM_2.5日均值 Daily mean value of PM_2.5/(μg∙m^-3)
0	0
50	35
100	75
150	115
200	150
300	250
400	350
500	500

因变量Dependent variable	预测变量 Predictor variable	非标准化系数 Non-standardized coefficient		标准系数 Standard coefficient	sig.	R²
因变量Dependent variable	预测变量 Predictor variable	常量B	标准误差 Standard error	回归系数 Beta	sig.	R²
PM_2.5	Constant	-587.922	52.439		0.000	0.532
	Temperature	23.346	2.561	0.547	0.000
	Humidity	6.637	0.495	0.805	0.000

因变量Dependent variable	预测变量 Predictor variable	非标准化系数 Non-standardized coefficient		标准系数 Standard coefficient	sig.	R²
因变量Dependent variable	预测变量 Predictor variable	常量B	标准误差 Standard error	回归系数 Beta	sig.	R²
PM_2.5	Constant	-587.922	52.439		0.000	0.532
	Temperature	23.346	2.561	0.547	0.000
	Humidity	6.637	0.495	0.805	0.000

街道峡谷选点位置 Street canyon location	ρ_(PM2.5)/ (μg∙m^-3)	AQI	空气质量水平 Air quality level	空气质量级别 Air quality level
A	132.26	174	Moderate pollution	Fourth level
B	123.90	162	Moderate pollution	Fourth level
C	128.14	168	Moderate pollution	Fourth level
D	151.09	201	Severe pollution	Fifth level
E	127.62	168	Moderate pollution	Fourth level
F	104.36	136	Light pollution	Third level
G	111.42	145	Light pollution	Third level
H	126.20	166	Moderate pollution	Fourth level