北京城市格局对空气NO2和O3分布的影响
文献类型：学位论文
| 作者 | 杨绍顺 |
| 学位类别 | 硕士 |
| 答辩日期 | 2014-05 |
| 授予单位 | 中国科学院研究生院 |
| 授予地点 | 北京 |
| 导师 | 欧阳志云 |
| 关键词 | 被动式采样 城市格局 土地利用回归模型 景观格局指数 NO2 O3 passive sampling urban patterns LUR model landscape metrics NO2 O3 |
| 其他题名 | The Effects of Urban Patterns on Distributions of Nitrogen Dioxide and Ozone in Beijing |
| 学位专业 | 生态学 |
| 中文摘要 | 随着人口在城市的集中，人类活动所造成的影响越来越严重，一方面直接作用于城市环境，更多的是通过改造城市下垫面来影响区域的物质能量流，进而影响整个生态过程。目前城市环境面临形势严峻，空气、水及垃圾等的污染都不容乐观。对大气环境而言主要问题是，不断增长的能源消耗和机动车辆加重了中国城市大气环境的负担，光化学污染和颗粒物污染替代煤烟污染成为了主要污染类型，表现为城市和区域大气环境中细粒子和臭氧浓度升高，阴霾天气频发，大气环境的氧化性和酸性增高，对城市大气环境研究提出了新的要求。 本文选取北京市五环范围为研究区域，选用在环境安全和流行病学领域广泛应用的被动式采样器为定量监测手段，选取NO2 和O3 作为大气污染物的表征，分析污染物的时空分布格局，建立土地利用回归模型，绘制高精度的污染物分布图；并将景观生态学原理引入城市大气环境中，探索格局与效应之间的作用机制。研究结果以及结论如下： （1）利用Ogawa 大气被动式采样器在2011 年9 月期间，采用网格随机的方法对北京市五环范围内的整体NO2 分布进行了测定，其平均值为0.69mg/m3，远高于同期城市环境监测站； （2） 利用GIS 和RS 建立NO2 浓度与地理环境因素的相关关系，建立LUR模型，最终模型中包含5 个独立的预测变量，R2=0.680。并与12 个主动监测站数进行比对，其R2=0.7154； （3）利用LUR 模型绘制的NO2 浓度分布图显示，北京市秋季NO2 浓度分布总体呈环状分布，南北不对称，市中心到郊区污染物呈现倒U 型曲线，三环四环区域污染物浓度最高。 （4）在以陶然亭为中心的3×3km 的小尺度范围布置了49 个O3 采样点，结果显示，其平均浓度为0.052 mg/m3，低于国家空气质量二级标准。分析景观指数与O3 浓度直接的关系显示，O3 浓度与平均斑块大小、聚集度指数、不透水面比例、相似百分比等景观格局均显著相关。 |
| 英文摘要 | Growing with rapid urbanization and concentration of urban population, citizens in cities are playing increasingly important roles in alternation of urban environment.On the one hand directly into the urban environment, and more through construction urban underlying surface to influence regional material and energy flows, thereby affecting the entire ecological processes. At present the urban atmospheric environment faces the tough situation, rising energy consumption and growing motor vehicles increased the burden of the urban atmospheric environment. As for Beijing, photochemical pollution and particulate pollution become a major types of pollution instead of soot pollution. In order to estimate the spatial variation within well-defined study areas,nitrogen dioxide and ozone were measured with diffusion passive samplers (Ogawa tube) in 49-139 sites in Beijing built-in areas. To capture the fine spatial variation and mapping the pollution distribution, we developed regression equations to predict fine Nitrogen Dioxide (NO2) in passive sampling locations in Beijing built areas using data on nearby traffic and land use patterns. And the principles of landscape ecology will be introduced in the study, to explore the mechanism between “pattern and effect”. The results are as follows: (1) We studied the whole NO2 distribution in 139 different sampling sites within the scope of Beijing five rings. The sampling sites were selected randomly in grids of Beijing map and the weekly average values was 0.068mg/m3,much higher than the values reported by the urban monitoring networks. (2) We modeled traffic-related NO2 by Land use regression to explore the relationship between the distribution and nearby geographic variables. The final regression model for the NO2 concentration included five independent variables, and explained 68.0% of the variation of NO2.Comparing to the results of 12 fixed-monitor sites, the predicted concentration has a significantly correlated with actual values(R2=0.7154). (3) From this a regression model was created that predicts the level of the contaminant at any site in the region based on the geographic predictors. A pollution surface map, which is a visual representation of the regression model, can then be generated. We found NO2 concentration show cricoid distribution, north and south asymmetry. The downtown to the suburbs contaminants present pour U curve, the highest concentration areas were between the three-ring and the fourth-ring road. (4) We developed an empirical study of the impact of urban development patterns on atmosphere pollutant (ozone) in 26 areas around the Taoranting Park on a gradient of urbanization. The weekly average value was 0.052 mg/m3, below the national air quality secondary standard. Significant statistical relationships were found between landscape patterns—both amount and configuration of impervious areas and forest land—and ozone concentration suggesting that patterns of urban development matter to atmosphere environment. |
| 公开日期 | 2015-06-12 |
| 源URL | [http://ir.rcees.ac.cn/handle/311016/13454]  |
| 专题 | 生态环境研究中心_城市与区域生态国家重点实验室 |
| 推荐引用方式 GB/T 7714 | 杨绍顺. 北京城市格局对空气NO2和O3分布的影响[D]. 北京. 中国科学院研究生院. 2014. |
入库方式： OAI收割
来源：生态环境研究中心
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