| 城市慢行道路中交通颗粒物的时空分布 |
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| 引用本文： | 罗斌儒,曹如晖,陈昕,胡喜生,王占永. 城市慢行道路中交通颗粒物的时空分布[J]. 上海大学学报(自然科学版), 2021, 28(4): 582-593. DOI: 10.12066/j.issn.1007-2861.2351 |
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| 作者姓名： | 罗斌儒 曹如晖 陈昕 胡喜生 王占永 |
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| 作者单位： | 福建农林大学 交通与土木工程学院, 福建 福州 350108 |
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| 基金项目： | 国家自然科学基金资助项目(41701552);福建省自然科学基金资助项目(2021J01105) |
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| 摘 要： | 为了捕捉城市慢行道路中空气污染的高时空分辨率特征, 构建了基于微型传感器的骑行测量平台, 通过收集福州市西三环快速路沿侧慢行道亚微米颗粒物(PM1.0)和黑碳 (black carbon, BC) 的质量浓度样本, 可视化解析交通污染的时空变化及原因. 研究表明: 慢行道的颗粒物质量浓度整体呈现小区侧大于沿江侧, 交通早、晚高峰大于中午; 早高峰 BC 稳定聚集但 PM1.0 波动较大, 晚高峰则相反; 慢行道颗粒物的质量浓度下降与临近主干道的距离、植被丰度正相关; 颗粒物冷点距离干道远且四周植被覆盖高, 热点多分布在施工与拥堵的复杂交通环境中; BC 热点与复杂路况同步, 但 PM1.0 热点还与周围环境相关. 因此, 有必要聚焦道路交通排放的主要构成, 并结合局部地形、空间、环境等因素来改善慢行道空气质量, 从而提升健康出行品质.
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| 关 键 词： | 大气颗粒物 时空分布 移动测量 慢行交通 |
| 收稿时间： | 2021-09-07 |
Spatiotemporal distribution of traffic particulate matter in urban non-motorized lanes |
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| LUO Binru,CAO Ruhui,CHEN Xin,HU Xisheng,WANG Zhanyong. Spatiotemporal distribution of traffic particulate matter in urban non-motorized lanes[J]. Journal of Shanghai University(Natural Science), 2021, 28(4): 582-593. DOI: 10.12066/j.issn.1007-2861.2351 |
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| Authors: | LUO Binru CAO Ruhui CHEN Xin HU Xisheng WANG Zhanyong |
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| Affiliation: | College of Transportation and Civil Engineering, Fujian Agriculture and Forestry University, Fuzhou 350108, Fujian, China |
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| Abstract: | To capture the high temporal and spatial resolution characteristics of air pollution in urban non-motorized lanes, a micro-sensor-based cycling measurement platform was established to collect samples of submicron particulate matter (PM1.0 ) and black carbon (BC) in non-motorized lanes alongside an expressway in Fuzhou, China. The temporal and spatial variations of these traffic particles were then visually analyzed, and explanations were provided. Results showed that the concentrations of PM1.0 and BC were significantly greater along the community side than on the river side and were greater in the morning and evening peak periods than in the noon. In the morning, the BC concentration showed a stable accumulation, but PM1.0 had a greater volatility; the opposite was the case in the evening. The drop of particulate matter concentration in non-motorized lanes was positively correlated with the distance to the main road and the abundance of vegetation around. The cold spots of particles were far from the main road and near high vegetation coverage, whereas hot spots were mostly distributed in traffic environments with construction and congestion. BC hotspots were synchronized with complex road conditions, but PM1.0 hotspots were also closely related to the surrounding environment. Therefore, focusing on the key traffic pollutants is necessary in designing show-moving traffic while considering the topographical characteristics, spatial conditions, and surrounding environment. This can improve air quality in non-motorized lanes, thereby enhancing healthy commuting. |
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| Keywords: | atmospheric particulate matter temporal and spatial distribution mobile measurement show-moving traffic |
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