| 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 |
| 摘要点击 1839 全文点击 817 投稿时间：2017-05-03 修订日期：2017-06-09 |
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| 中文关键词 黑碳浓度 土地利用回归模型 空间分异 移动样带监测 上海市 |
| 英文关键词 black carbon concentration land use regression model spatial variation mobile monitoring Shanghai |
| 作者 | 单位 | E-mail | | 彭霞 | 华东师范大学地理科学学院, 上海 200241
华东师范大学上海市城市化生态过程与生态恢复重点实验室, 上海 200241 | claire_px@126.com | | 佘倩楠 | 华东师范大学生态与环境科学学院, 上海 200241
华东师范大学上海市城市化生态过程与生态恢复重点实验室, 上海 200241 | | | 龙凌波 | 华东师范大学生态与环境科学学院, 上海 200241
华东师范大学上海市城市化生态过程与生态恢复重点实验室, 上海 200241 | | | 刘敏 | 华东师范大学生态与环境科学学院, 上海 200241
华东师范大学上海市城市化生态过程与生态恢复重点实验室, 上海 200241 | mliu@re.ecnu.edu.cn | | 徐茜 | 华东师范大学生态与环境科学学院, 上海 200241 | | | 魏宁 | 华东师范大学生态与环境科学学院, 上海 200241
华东师范大学上海市城市化生态过程与生态恢复重点实验室, 上海 200241 | | | 周陶冶 | 上海市浦东新区环境监测站, 上海 200135 | |
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| 中文摘要 |
| 黑碳（BC）是大气污染物的重要组成部分，对空气质量与人类生活健康产生重要的影响.本研究采用移动样带手段开展上海市近地面BC浓度监测，分析其基本统计特征和空间分异性.在此基础上，利用土地利用回归模型（LUR），探讨人口密度、经济产值和交通道路网密度等因素对上海市近地面BC浓度空间分异的影响.结果表明上海市近地面BC平均浓度为（9.86±8.68） μg·m-3，空间差异明显，郊区[（10.47±2.04） μg·m-3]比市中心地区[（7.93±2.79） μg·m-3]高32.03%（2.54μg·m-3）.气象要素（风速和相对湿度）和交通道路变量（路网长度、省道距离、高速距离等）显著影响上海市近地面BC浓度（r为0.5~0.7，P<0.01）.基于气象和交通道路变量的LUR模型能较好模拟上海近地面BC浓度（调整后R2为0.62~0.75，交叉验证R2为0.54~0.69，RMSE为0.15~0.20μg·m-3），其中100 m和5 km缓冲距离的LUR模型相对较优，在一定程度上表明上海市近地面BC浓度主要受气象要素和交通源的影响.本研究有利于加深对上海市BC浓度空间分布格局及其影响因素的客观认识，可为模拟和预测BC对人类活动和自然环境的响应机制提供科学依据和理论支撑. |
| 英文摘要 |
| Black carbon (BC) is an important component of atmospheric pollution and has significant impacts on air quality and human health. Choosing Shanghai city for a case study, this paper explores the statistical characteristics and spatial patterns of BC concentrations using a mobile monitoring method, which differs from traditional fixed-site observations. Land use regression (LUR) modeling was conducted to examine the determinants for on-road BC concentrations, e.g. population, economic development, traffic, etc. These results showed that the average on-road BC concentrations were (9.86±8.68) μg·m-3, with a significant spatial variation. BC concentrations in suburban areas[(10.47±2.04) μg·m-3] were 32.03% (2.54 μg·m-3) higher than those in the city center[(7.93±2.79) μg·m-3]. Besides, meteorological factors (e.g. wind speed and relative humidity) and traffic variables (e.g. the length of roads, distance to provincial roads, distance to highway) had significant effects on on-road BC concentrations (r:0.5-0.7, P<0.01). Moreover, the LUR model, including meteorological and traffic variables performed well (adjusted R2:0.62-0.75, cross validation R2:0.54-0.69, RMSE:0.15-0.20 μg·m-3), which demonstrates that on-road BC concentrations in Shanghai are mainly affected by these factors and traffic sources to some extent. Among them, the most accurate LUR model was developed with a 100 m buffer, followed by the LUR model with a 5 km buffer. This study is of great significance for the identification of spatial distribution patterns for on-road BC concentration and exploring their influencing factors in Shanghai, which can provide a scientific basis and theoretical support for simulating and predicting the response mechanisms of BC on human health and the natural environment. |
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