基于移动监测的城市环境大气黑碳浓度空间特征及来源解析

doi:10.13287/j.1001-9332.202208.023

应用生态学报 ›› 2022, Vol. 33 ›› Issue (8): 2221-2228.doi: 10.13287/j.1001-9332.202208.023

基于移动监测的城市环境大气黑碳浓度空间特征及来源解析

武秋彤^1,2, 刘敏^1,2,3*, 李舒惠^1,2, 高婵婵^1,2, 曹闪闪^1,2, 苏玲^1,2, 张世勍^1,2

¹华东师范大学生态与环境科学学院, 上海 200241;
²上海市城市化生态过程与生态恢复重点实验室, 上海 200241;
³崇明生态研究院, 上海 200062

收稿日期:2021-10-11 接受日期:2022-05-24 出版日期:2022-08-15 发布日期:2023-02-15
通讯作者: * E-mail: mliu@re.ecnu.edu.cn
作者简介:武秋彤, 女, 1998年生, 硕士研究生。主要从事城市生态学相关研究。E-mail: wqt980320@163.com
基金资助:
国家自然科学基金项目(41977399)资助。

Spatial characteristics and source apportionment of urban environmental black carbon concentrations based on mobile monitoring

WU Qiu-tong^1,2, LIU Min^1,2,3*, LI Shu-hui^1,2, GAO Chan-chan^1,2, CAO Shan-shan^1,2, SU Ling^1,2, ZHANG Shi-qing^1,2

¹School of Ecological and Environment Sciences, East China Normal University, Shanghai 200241, China;
²Shanghai Key Laboratory for Urban Ecological Processes and Eco-Restoration, Shanghai 200241, China;
³Institute of Eco-Chongming, Shanghai 200062, China

Received:2021-10-11 Accepted:2022-05-24 Online:2022-08-15 Published:2023-02-15

摘要/Abstract

摘要： 黑碳(BC)是大气细颗粒物的重要组分,对全球气候变化和人体健康有重要影响。本研究以上海市闵行区为研究区域,在电动出租车上安装MA200便携式黑碳仪和GPS定位系统组成移动观测平台,识别城市环境大气BC空间分布和热点区域,解析大气BC来源及影响因素。结果表明:上海市闵行区近地面大气BC空间分布格局总体呈现北高南低的特征,大气BC浓度平均值为(4.11±4.87) μg·m^-3,工作日与非工作日BC平均浓度分别为(4.22±1.49)和(3.52±2.26) μg·m^-3。大气BC浓度高值区变异性较大,移动观测中BC浓度升高与路段中交通偶发事件有关。除人类活动外,大范围的密集植被会对BC扩散产生抑制作用。波长吸收指数值为(0.82±0.54),更接近化石燃料燃烧波长吸收指数,化石燃料排放、生物质燃烧和混合源对于本研究中BC来源的贡献占比分别为67.5%、4.9%和27.6%。

关键词: 移动监测, 黑碳, 源解析, 城市环境, 上海

Abstract: Black carbon (BC) is an important component of airborne fine particulate matter, with significant impacts on global climate change and human health. Taking Minhang District of Shanghai as the study area, a microaethalometer (MA200) and GPS were installed on the electric taxi to form a mobile observation platform to identify the spatial distribution and hot spots of atmospheric BC in urban environment. We analyzed the sources and influencing factors of BC. The results showed that the overall characteristics of the spatial distribution pattern of near surface atmospheric BC in Minhang District of Shanghai were high in the north and low in the south. The average BC concentration was (4.11±4.87) μg·m^-3. The average concentrations of BC in working days and non-working days were (4.22±1.49) and (3.52±2.26) μg·m^-3. The variability of BC concentration in the high value area was large, indicating that the increases of BC concentration in mobile observation were related to traffic accidents in the road section. In addition to human activities, large-scale dense vegetation might inhibit BC diffusion. The Absorption ngström Exponent (AAE) was (0.82±0.54), which was closer to that of fossil fuel combustion. The contributions of fossil fuel emissions, biomass combustion, and mixed sources to BC sources were 67.5%, 4.9% and 27.6%, respectively.

Key words: mobile monitoring, black carbon, source apportionment, urban environment, Shanghai

武秋彤, 刘敏, 李舒惠, 高婵婵, 曹闪闪, 苏玲, 张世勍. 基于移动监测的城市环境大气黑碳浓度空间特征及来源解析[J]. 应用生态学报, 2022, 33(8): 2221-2228.

WU Qiu-tong, LIU Min, LI Shu-hui, GAO Chan-chan, CAO Shan-shan, SU Ling, ZHANG Shi-qing. Spatial characteristics and source apportionment of urban environmental black carbon concentrations based on mobile monitoring[J]. Chinese Journal of Applied Ecology, 2022, 33(8): 2221-2228.

参考文献

[1] Kirchstetter TW, Novakov T. Controlled generation of black carbon particles from a diffusion flame and applications in evaluating black carbon measurement me-thods. Atmospheric Environment, 2006, 41: 1874-1888
[2] 程丁, 吴晟, 吴兑, 等. 深圳市城区和郊区黑碳气溶胶对比研究. 中国环境科学, 2018, 38(5): 1653-1662
[3] 曹闪闪, 段玉森, 高婵婵, 等. 基于MERRA-2再分析资料的上海市近40年大气黑碳浓度变化及潜在来源解析. 环境科学, 2021, 42(6): 2668-2678
[4] 赵德华, 欧阳琰, 齐家国, 等. 夏季南京市中心-郊区-城市森林梯度上的近地层大气特征. 生态学报, 2009, 29(12): 6654-6663
[5] 白杨, 秦凯, 吴立新, 等. 徐州市区主干道路黑炭气溶胶浓度移动观测实验. 地理与地理信息科学, 2014, 30(1): 45-49
[6] Idso CD, Idso SB, Balling RC. The urban CO₂ dome of Phoenix, Arizona. Physical Geography, 1998, 19: 95-108
[7] Peters J, Theunis J, van Poppel M, et al. Monitoring PM₁₀ and ultrafine particles in urban environments using mobile measurements. Aerosol and Air Quality Research, 2013, 13: 509-522
[8] Liu XS, Zhang X, Schnelle-Kreis J, et al. Spatiotemporal characteristics and driving factors of black carbon in Augsburg, Germany: Combination of mobile monitoring and street view images. Environmental Science & Technology, 2020, 55: 160-168
[9] Targino AC, Krecl P, Danziger JE, et al. Spatial variability of on-bicycle black carbon concentrations in the megacity of Sao Paulo: A pilot study. Environmental Pollution, 2018, 242: 539-543
[10] Blanco-Donado EP, Schneider IL, Artaxo P, et al. Source identification and global implications of black carbon. Geoscience Frontiers, 2021, 12, doi: 10.1016/j.gsf.2021.101149
[11] DeSouza P, Lu RQ, Kinney P, et al. Exposures to multiple air pollutants while commuting: Evidence from Zhengzhou, China. Atmospheric Environment, 2020, 247, doi: 10.1016/j.atmosenv.2020.118168
[12] 李燕丽, 邢振雨, 穆超, 等. 移动监测法测量厦门春秋季近地面CO₂的时空分布. 环境科学, 2014, 35(5): 1671-1679
[13] 胡明玉, 秦凯, 白杨, 等. 2013年12月石家庄一次霾天气过程中的黑炭浓度特征. 中国环境科学, 2015, 35(9): 2585-2593
[14] Hankey S, Marshall JD. On-bicycle exposure to parti-culate air pollution: Particle number, black carbon, PM_2.5, and particle size. Atmospheric Environment, 2015, 122: 65-73
[15] Targino AC, Gibson MD, Krecl P, et al. Hotspots of black carbon and PM_2.5 in an urban area and relationships to traffic characteristics. Environmental Pollution, 2016, 218: 475-486
[16] Van den Bossche J, De Baets B, Verwaeren J, et al. Development and evaluation of land use regression models for black carbon based on bicycle and pedestrian measurements in the urban environment. Environmental Modelling and Software, 2018, 99: 58-69
[17] Feng JL, Zhong M, Xu BH, et al. Concentrations, seasonal and diurnal variations of black carbon in PM_2.5 in Shanghai, China. Atmospheric Research, 2014, 147: 1-9
[18] 上海市闵行区人民政府. 2021年闵行统计年鉴[EB/OL]. (2021-09-13) [2021-12-02]. http://www.shmh.gov.cn/shmh/tjnj/20210913/527986.html
[19] 上海市人民政府. 上海市城市规划管理技术规定(土地使用建筑管理)[EB/OL]. (2003-10-18) [2021-12-02]. https://www.shanghai.gov.cn/nw12939/20200815/0001-12939972.html
[20] 韩玥枫. 论上海城市林荫道建设中的行道树树种选择. 中国园林, 2019, 35(增刊2): 80-83
[21] 上海市闵行区统计局. 2020年上海市闵行区国民经济和社会发展统计公报[EB/OL]. (2021-03-23) [2021-10-10]. http://www.shmh.gov.cn/shmh/tjsj-tjgb/20210323/516315.html
[22] 环评互联网. 世界卫生组织发布新的空气质量准则[EB/OL]. (2021-10-05) [2021-12-02]. https://baijiahao.baidu.com/s?id=1712745028000084165&wfr=spider&for=pc
[23] 周变红, 曹夏, 张容端, 等. 宝鸡高新区黑碳气溶胶浓度特征及其影响因素研究. 中国环境监测, 2021, 37(5): 125-132
[24] Sandradewi J, Prevot ASH, Szidat S, et al. Using aerosol light absorption measurements for the quantitative determination of wood burning and traffic emission contributions to particulate matter. Environmental Science & Technology, 2008, 42: 3316-3323
[25] Day DE, Hand JL, Carrico CM, et al. Humidification factors from laboratory studies of fresh smoke from biomass fuels. Journal of Geophysical Research: Atmospheres, 2006, 111, doi: 10.1029/2006JD007221
[26] 章基嘉, 孙照渤, 陈松军. 应用K均值聚类法对东亚各自然天气季节500毫巴候平均环流的分型试验. 气象学报, 1984, 42(3): 311-319
[27] Bos B, Lim S, Hedges M, et al. Taxi drivers' exposure to black carbon and nitrogen dioxide in electric and diesel vehicles: A case study in London. Environmental Research, 2021, 195, doi: 10.1016/j.envres.2021.110736
[28] Jereb B, Batkovic T, Herman L, et al. Exposure to black carbon during bicycle commuting-alternative route selection. Atmosphere, 2018, 9, doi: 10.3390/atmos9010021
[29] Luengo-Oroz J, Reis S. Assessment of cyclists' exposure to ultrafine particles along alternative commuting routes in Edinburgh. Atmospheric Pollution Research, 2019, 10: 1148-1158
[30] Liu M, Peng X, Meng ZQ, et al. Spatial characteristics and determinants of in-traffic black carbon in Shanghai, China: Combination of mobile monitoring and land use regression model. Science of the Total Environment, 2018, 658, doi: 10.1016/j.scitotenv.2018.12.135
[31] 彭霞, 佘倩楠, 龙凌波, 等. 基于移动监测和土地利用回归模型的上海市近地面黑碳浓度空间模拟. 环境科学, 2017, 38(11): 4454-4462
[32] Lei XN, Bian JW, Xiu GL, et al. The mobile monitoring of black carbon and its association with roadside data in the Chinese megacity of Shanghai. Environmental Science and Pollution Research, 2017, 24: 7482-7489
[33] Van den Bossche J, Theunis J, Elen B, et al. Opportunistic mobile air pollution monitoring: A case study with city wardens in Antwerp. Atmospheric Environment, 2016, 141: 408-421
[34] Dons E, Temmerman P, Van Poppel M, et al. Street characteristics and traffic factors determining road users' exposure to black carbon. Science of the Total Environment, 2013, 447: 72-79
[35] Becerril-Valle M, Coz E, Prevot ASH, et al. Characte-rization of atmospheric black carbon and co-pollutants in urban and rural areas of Spain. Atmospheric Environment, 2017, 169: 36-53
[36] Favez O, Cachier H, Sciare J, et al. Evidence for a significant contribution of wood burning aerosols to PM_2.5 during the winter season in Paris, France. Atmospheric Environment, 2009, 43: 3640-3644

基于移动监测的城市环境大气黑碳浓度空间特征及来源解析

Spatial characteristics and source apportionment of urban environmental black carbon concentrations based on mobile monitoring

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	赵铖钰, 张淑怡, 朱泓恺, 谷璇, 刘敏. 上海地表热环境演变趋势城乡分异及其对城市更新的响应 [J]. 应用生态学报, 2023, 34(7): 1923-1931.
[2]	闫玉玉, 孙彦伟, 刘敏. 基于生态安全格局的上海国土空间生态修复关键区域识别与修复策略 [J]. 应用生态学报, 2022, 33(12): 3369-3378.
[3]	谢汉宾, 张伟, 李贲, 李必成, 张云飞, 王天厚. 两栖类栖息地的构建技术及效果评估 [J]. 应用生态学报, 2018, 29(8): 2771-2777.
[4]	王美雅, 徐涵秋. 上海和纽约城市不透水面时空变化及其对生态质量影响的对比 [J]. 应用生态学报, 2018, 29(11): 3735-3746.
[5]	梁宪萌, 宋金明, 袁华茂, 李学刚, 李宁, 段丽琴. 固体介质中的重金属源解析及其在中国近海沉积物中的应用 [J]. 应用生态学报, 2017, 28(9): 3087-3098.
[6]	伍海兵, 周建强, 方海兰. 上海中心城区绿地土壤水库特征 [J]. 应用生态学报, 2017, 28(3): 966-974.
[7]	徐嘉晖,高雷,崔晓阳. 大兴安岭中段森林土壤的黑碳含量及其在不同粒级中的分布 [J]. 应用生态学报, 2017, 28(10): 3111-3118.
[8]	潘晨1,2,朱希扬1,3,贾文晓1,3,杨芳1,3,刘敏1,3**,象伟宁1,3. 上海市近地面CO₂浓度及其与下垫面特征的定量关系 [J]. 应用生态学报, 2015, 26(7): 2123-2130.
[9]	陈立婧1,吴艳芳1,景钰湘1,王聪. 上海世博园后滩湿地枝角类群落结构的周年动态 [J]. 应用生态学报, 2012, 23(10): 2863-2870.
[10]	史利江,郑丽波,梅雪英,俞立中,贾正长. 上海市不同土地利用方式下的土壤碳氮特征 [J]. 应用生态学报, 2010, 21(09): 2279-2287.
[11]	曹建军,刘永娟. GIS支持下上海城市生态敏感性分析 [J]. 应用生态学报, 2010, 21(07): 1805-1812.
[12]	古志钦;张利权;袁琳. 互花米草与芦苇光合色素含量对淹水措施的响应 [J]. 应用生态学报, 2009, 20(10): 2365-2369.
[13]	宋坤;秦俊;高凯;胡永红. 上海居住区植物多样性的均质化 [J]. 应用生态学报, 2009, 20(07): 1603-1607 .
[14]	徐曦^2,3;王小明^1,3;王天厚^1,3;刘益宁⁴;王开运^2,3. “千层饼”模式在上海世界博览会区域生态规划前期研究中的应用 [J]. 应用生态学报, 2009, 20(05): 1132-1139 .
[15]	曹丹^1,2;周立晨^1,2;毛义伟^1,2;李胤^1,2;刘益宁^1,2;王天厚^1,2. 上海城市公共开放空间夏季小气候及舒适度 [J]. 应用生态学报, 2008, 19(08): 1797-1802 .