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| 基于健康损失的峡谷型路段环境交通阻抗模型 | |
| 引用本文： | 王希伟,李铁柱,汪林,李斌,何炜.基于健康损失的峡谷型路段环境交通阻抗模型[J].东南大学学报(自然科学版),2010,40(1). |
| 作者姓名： | 王希伟 李铁柱 汪林 李斌 何炜 |
| 作者单位： | 1. 东南大学交通学院,南京,210096 2. 交通运输部公路科学研究院国家智能交通系统工程技术研究中心,北京,100088 3. 许昌市规划设计院,许昌,461000 |
| 基金项目： | 国家自然科学基金资助项目(50778041,50608018);;江苏省建设系统科技计划资助项目(JS2007JH21);;智能交通关键技术交通行业重点实验室开放基金资助项目(2009ITS-KL-001) |
| 摘 要： | 运用广义阻抗模型的思想构建峡谷型路段的环境交通阻抗模型.首先给出峡谷型路段底部污染物浓度计算方法.忽略环境因素对污染物垂直分布的影响,运用数值拟合方法,对现有实验数据进行一元非线性拟合,得到峡谷型路段污染物浓度垂直分布特性.运用污染物浓度与健康效应的剂量-反应关系(C-R)函数,定量分析城市大气污染物对城市居民健康的影响,并在此基础上运用支付意愿法,对污染物单位排放量造成的健康损失进行货币化;在传统的BPR路段阻抗函数的基础上构造基于健康损失的峡谷型路段广义阻抗模型.以CO作为污染物建立广义阻抗并对其特性进行分析.研究表明:基于健康损失的广义阻抗主要贡献来源于健康损失部分,在当量交通量一定但车型比例不同的条件下,由BPR函数确定的狭义阻抗是定值,但是由于机动车尾气排放因子不同,广义阻抗会随着车型比例变化而变化. |
| 关 键 词： | 广义阻抗模型 健康损失 街道峡谷污染物扩散模式 C-R模型 |
Environmental traffic impedance model of street canyon based on health impacts |
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| Wang Xiwei,Li Tiezhu,Wang Lin,Li Bin,He Wei.Environmental traffic impedance model of street canyon based on health impacts[J].Journal of Southeast University(Natural Science Edition),2010,40(1). | |
| Authors: | Wang Xiwei Li Tiezhu Wang Lin Li Bin He Wei |
| Institution: | 1School of Transportation;Southeast University;Nanjing 210096;China;2 National Intelligent Transport Systems Center of Engineering and Technology;Research Institute of Highway of Ministry of Transport;Beijing 100088;China;3Xuchang Planning and Design Institute;Xuchang 461000;China |
| Abstract: | An environmental traffic impedance model is constructed based on generalized impedance.First,a method of calculating pollutant concentration on the bottom of street is given.Then vertical distribution of pollutant concentration is obtained through unitary nonlinear fitting.Healthy effect caused by atmosphere pollutant is quantitatively analyzed by using concentration-response relationship between pollutant concentration and healthy effect,and then this healthy effect is monetized by willing payment method.G... |
| Keywords: | generalized impedance model health impacts OSPM (operational street pollution model) C-R model |
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