中文摘要：

城市化所带来的土地利用变化和化石燃料燃烧对全球碳循环和气候变化产生了深远影响.明确城市区域CO2浓度的空间变化特征,对于认识和控制温室气体排放、减少人类活动对全球气候变化的影响具有重要意义.本研究以高强度人类扰动和快速城市化背景下的上海市为研究对象,于2014年春季利用近红外气体分析仪Li-840A开展近地面CO2浓度样带监测,结合遥感数据获取的城市下垫面特征信息,在明确上海市近地面CO2浓度空间分布格局的基础上,进一步定量分析其对城市下垫面特征的响应机制.结果表明：上海市近地面CO2浓度为（443.4±22.0）μmol·mol-1,城市中心CO2浓度比郊区平均高12.5%（52.5μmol·mol-1）.近地面CO2浓度空间异质性显著,呈现西北高、西南次之、东南低的趋势,总体表现为随着下垫面城市化水平的降低而降低.城市下垫面植被覆盖率（CVeg）是城市近地面CO2浓度的重要指示因子,两者呈现负相关;不透水层覆盖率（CISA）次之,两者呈正相关.CO2浓度（CCO2）与CISA及CVeg的相关性（R2）在缓冲距离为5 km时同时达到峰值,三者之间的定量关系可通过建立逐步回归方程表征：CCO2=0.32CISA-0.89CVeg＋445.13（R2=0.66,P〈0.01）.

英文摘要：

Land use change and fossil fuel combustion due to urbanization have a significant effect on global carbon cycle and climate change. It＇ s important to have an explicit understanding of the spatial distribution of CO2 to recognize and control GHG emission, which is helpful to reduce human-induced contribution to global climate change. The study area of this project was set in the city of Shanghai with intensive human activity and rapid urbanization. The monitoring of near surface CO2 concentration along 3 transects was conducted across an urban-rural gradient by means of near infrared gas analyzer Li-840A in spring, 2014. Remote sensing data were also used to derive under- lying surface information. Further quantitative analysis of the mechanism of CO2 concentration＇ s response to the characteristics of underlying surface was presented in this paper. The results showed that the average near surface CO2 concentration was （443.4＋22.0） μmol · tool-1. CO2 concentration in city center was in average 12.5% （52.5 μmol· tool-l） higher than that in the suburban area. Al- so, CO2 concentration showed a significant spatial differentiation, with the highest CO2 concentra- tion in the northwest, the second highest in the southwest, and the lowest in the southeast, which was in accordance with the urbanization level of the underlying surface. The results revealed that thevegetation coverage rate （Cves） was an important indicator to describe near surface CO2 concentra- tion with a negative correlation, and the impervious surface area coverage rate （CisA） had lower ex- planatory power with a positive correlation. The study also found that the determination coefficient （R2 ） between CO2 concentration （Cco2） and CISA or Cws achieved its highest value when the buffer distance was 5 kin, and their quantitative relationships be described by a stepwise regression equa- tion ： Cco2 = 0.32CISA-0.89Cveg＋445.13 （R2 = 0.66, P〈0.01 ）.