Methodological study and application of advanced receptor modeling to airborne particulate sources

Two aspects of air quality management, aerosol mass measurement and pollution source identification, were studied. A beta gauge was developed to determine particulate mass collected on filter. Two advanced receptor models were applied to resolve possible sources of pollutants on local and regional scales by use of positive matrix factorization (PMF) and multilinear engine (ME), respectively.; A simple, low cost beta gauge was designed, constructed, and tested to determine if it provided the necessary performance and reliability in collected aerosol mass measurements. The beta gauge was calibrated and evaluated by experiments with different sized particles. The results showed that the unit provided a satisfactory accuracy and precision with respect to the gravimetric method.; (PMF) is a least-square approach to factor analysis. In this study, PMF was applied to investigate the possible sources of airborne particulate matter (APM) collected at an urban residential area of Bangkok from June 1995 to May 1996 and at a suburban residential area in Pathumthani from September 1993 to August 1994. The data consisting of the fine and coarse fractions were analyzed separately. The analysis used the robust analysis mode and rotations to produce six source factors for both the fine and coarse fractions at the urban site and five factors for the fine and coarse fractions at the suburban site. Examination of the influence of wind direction showed the correspondence of some specific factors such as sea salt and vehicle sources with known area sources.; ME is a new algorithm for solving a broad range of multilinear problems. A model was developed for the analysis of spatial patterns and possible sources affecting haze and its visual effects in the southwestern United States. The data from the project Measurement of Haze and Visual Effects (MOHAVE) collected during the late winter and mid-summer of 1992 at the monitoring sites in four states, i.e., California, Arizona, Nevada and Utah, were used in the study. The 3-way data array was analyzed by 4-product term model. A feature of the model is that the wind pattern is included to investigate the spatial pattern of each source identified. For winter data set reasonable solutions contained six sources and six wind patterns. The analysis of summer data required seven sources and seven wind patterns. Back trajectories were calculated and plotted to compare to ME results to better understand the transport pathways.