Kim Eugene, Hopke Philip K, Larson Timothy V, Covert David S
Department of Civil and Environmental Engineering, Clarkson University, Box 5708, Potsdam, New York 13699, USA.
Environ Sci Technol. 2004 Jan 1;38(1):202-9. doi: 10.1021/es030310s.
Hourly averaged particle size distributions measured at a centrally located urban site in Seattle were analyzed through the application of bilinear positive matrix factorization (PMF) and Unmix to study underlying size distributions and their daily patterns. A total of 1051 samples each with 16 size intervals from 20 to 400 nm were obtained from a differential mobility particle sizer operating between December 2000 and February 2001. Both PMF and Unmix identify four similar underlying factors in the size distributions. Factor 1 is an accumulation mode particle size spectrum that shows a regular nocturnal pattern, and factor 2 is a larger particle distribution. Factor 3 is assigned as a traffic-related particle distribution, based on its correlations with accompanying gas-phase measurements, and has a regular weekday-high rush-hour pattern. Factor 4 is a traffic-related particle size distribution that has a regular rush-hour pattern on weekdays as well as weekends. Conditional probability functions (CPF) were computed using wind profiles and factor contributions. The results of CPF analysis suggest that these factors are correlated with surrounding particle sources of wood burning, secondary aerosol, diesel emissions, and motor vehicle emissions.
通过应用双线性正定矩阵因子分解(PMF)和非负矩阵分解(Unmix)方法,对在西雅图市中心一个城市站点测量的每小时平均粒径分布进行了分析,以研究潜在的粒径分布及其每日模式。在2000年12月至2001年2月期间,使用差分迁移率粒度分析仪共获得了1051个样本,每个样本有16个从20到400纳米的粒径区间。PMF和Unmix都在粒径分布中识别出四个相似的潜在因子。因子1是一种累积模态粒径谱,呈现出规律的夜间模式,因子2是较大颗粒的分布。基于因子3与伴随气相测量的相关性将其指定为与交通相关的颗粒分布,并且具有规律的工作日高峰时段模式。因子4是一种与交通相关的粒径分布,在工作日以及周末都有规律的高峰时段模式。使用风廓线和因子贡献计算了条件概率函数(CPF)。CPF分析结果表明,这些因子与木材燃烧、二次气溶胶、柴油排放和机动车排放等周围颗粒源相关。