Su Jason G, Brauer Michael, Ainslie Bruce, Steyn Douw, Larson Timothy, Buzzelli Michael
Department of Geography, University of British Columbia, Vancouver, British Columbia, Canada V6T 1Z2.
Sci Total Environ. 2008 Feb 15;390(2-3):520-9. doi: 10.1016/j.scitotenv.2007.10.032. Epub 2007 Nov 28.
The advent of spatial analysis and geographic information systems (GIS) has led to studies of chronic exposure and health effects based on the rationale that intra-urban variations in ambient air pollution concentrations are as great as inter-urban differences. Such studies typically rely on local spatial covariates (e.g., traffic, land use type) derived from circular areas (buffers) to predict concentrations/exposures at receptor sites, as a means of averaging the annual net effect of meteorological influences (i.e., wind speed, wind direction and insolation). This is the approach taken in the now popular land use regression (LUR) method. However spatial studies of chronic exposures and temporal studies of acute exposures have not been adequately integrated. This paper presents an innovative LUR method implemented in a GIS environment that reflects both temporal and spatial variability and considers the role of meteorology. The new source area LUR integrates wind speed, wind direction and cloud cover/insolation to estimate hourly nitric oxide (NO) and nitrogen dioxide (NO(2)) concentrations from land use types (i.e., road network, commercial land use) and these concentrations are then used as covariates to regress against NO and NO(2) measurements at various receptor sites across the Vancouver region and compared directly with estimates from a regular LUR. The results show that, when variability in seasonal concentration measurements is present, the source area LUR or SA-LUR model is a better option for concentration estimation.
空间分析和地理信息系统（GIS）的出现，促使人们基于城市内部环境空气污染浓度差异与城市间差异一样大这一原理，开展了关于长期暴露与健康影响的研究。此类研究通常依靠从圆形区域（缓冲区）得出的局部空间协变量（如交通、土地利用类型）来预测受体站点的浓度/暴露情况，以此平均气象影响（即风速、风向和日照）的年度净效应。这就是目前流行的土地利用回归（LUR）方法所采用的途径。然而，长期暴露的空间研究和急性暴露的时间研究尚未得到充分整合。本文介绍了一种在GIS环境中实施的创新型LUR方法，该方法既反映了时间和空间变异性，又考虑了气象因素的作用。新的源区域LUR整合了风速、风向和云量/日照，以根据土地利用类型（即道路网络、商业用地）估算每小时的一氧化氮（NO）和二氧化氮（NO₂）浓度，然后将这些浓度用作协变量，对温哥华地区各个受体站点的NO和NO₂测量值进行回归分析，并直接与常规LUR的估算值进行比较。结果表明，当季节性浓度测量存在变异性时，源区域LUR或SA - LUR模型是浓度估算的更佳选择。
