首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Integrating remote sensing and local vegetation information for a high-resolution biogenic emissions inventory--application to an urbanized, semiarid region
Authors:Diem J E  Comrie A C
Institution:Department of Geography and Regional Development, University of Arizona, Tucson. diem@climate.geog.arizona.edu
Abstract:This paper presents a methodology for the development of a high-resolution (30-m), standardized biogenic volatile organic compound (BVOC) emissions inventory and a subsequent application of the methodology to Tucson, AZ. The region's heterogeneous vegetation cover cannot be modeled accurately with low-resolution (e.g., 1-km) land cover and vegetation information. Instead, local vegetation data are used in conjunction with multispectral satellite data to generate a detailed vegetation-based land-cover database of the region. A high-resolution emissions inventory is assembled by associating the vegetation data with appropriate emissions factors. The inventory reveals a substantial variation in BVOC emissions across the region, resulting from the region's diversity of both native and exotic vegetation. The importance of BVOC emissions from forest lands, desert lands, and the urban forest changes according to regional, metropolitan, and urban scales. Within the entire Tucson region, the average isoprene, monoterpene, and OVOC fluxes observed were 454, 248, and 91 micrograms/m2/hr, respectively, with forest and desert lands emitting nearly all of the BVOCs. Within the metropolitan area, which does not include the forest lands, the average fluxes were 323, 181, and 70 micrograms/m2/hr, respectively. Within the urban area, the average fluxes were 801, 100, and 100 micrograms/m2/hr, respectively, with exotic trees such as eucalyptus, pine, and palm emitting most of the urban BVOCs. The methods presented in this paper can be modified to create detailed, standardized BVOC emissions inventories for other regions, especially those with spatially complex vegetation patterns.
Keywords:
本文献已被 PubMed 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号