The comprehensive application of different multivariate methods and geographic information systems (GIS) was used to evaluate the spatio-temporal patterns and source apportionment of coastal water pollution in eastern Hong Kong. Fourteen variables were surveyed at 27 sites monthly from 2000 to 2004. After data pretreatment, cluster analysis grouped the 12 months into two groups, June-September and the remaining months, and divided the entire area into two parts, representing different pollution levels. Discriminant analysis determined that NO3- -N, DO, and temperature and TN, SD, pO(4)(3-) -P, and VSS were 4 significant variables affecting temporal and spatial variations with 84% and 90% correct assignments, respectively Five potential pollution sources were identified for each part by rotated principal component analysis, explaining 71% and 68% of the total variances, respectively. Receptor-based source apportionment revealed that most of the variables were primarily influenced by soil weathering and organic pollution, nutrient pollution (or agricultural runoff), and mineral pollution. Furthermore, GIS further facilitated and supported multivariate analysis results. (C) 2007 Elsevier Ltd. All rights reserved.
[1] Fine particle organic carbon in Delhi, Mumbai, Kolkata, and Chandigarh is speciated to quantify sources contributing to fine particle pollution. Gas chromatography/mass spectrometry of 29 particle-phase organic compounds, including n-alkanes, polycyclic aromatic hydrocarbons (PAHs), hopanes, steranes, and levoglucosan along with quantification of silicon, aluminum, and elemental carbon are used in a molecular-marker based source apportionment model to quantify the primary source contributions to the PM2.5 mass concentrations for four seasons in three sites and for the summer in Chandigarh. Five primary sources are identified and quantified: diesel engine exhaust, gasoline engine exhaust, road dust, coal combustion, and biomass combustion. Important trends in the seasonal and spatial patterns of the impact of these five sources are observed. On average, primary emissions from fossil fuel combustion (coal, diesel, and gasoline) are responsible for about 25–33% of PM2.5 mass in Delhi, 21–36% in Mumbai, 37–57% in Kolkata, and 28% in Chandigarh. These figures can be compared to the biomass combustion contributions to ambient PM2.5 of 7–20% for Delhi, 7–20% for Mumbai, 13–18% for Kolkata, and 8% for Chandigarh. These measurements provide important information about the seasonal and spatial distribution of fine particle phase organic compounds in Indian cities as well as quantifying source contributions leading to the fine particle air pollution in those cities.
The formation of secondary organic aerosol (SOA) in an anthropogenic-influenced region in the southeastern United States is investigated by a comparison with urban plumes in the northeast. The analysis is based on measurements of fine-particle organic compounds soluble in water (WSOC) as a measure of secondary organic aerosol. Aircraft measurements over a large area of northern Georgia, including the Atlanta metropolitan region, and in plumes from New York City and surrounding urban regions in the northeast show that fine-particle WSOC are spatially correlated with vehicle emission tracers (e.g., CO), yet the measurements indicate that vehicles do not directly emit significant particulate WSOC. In addition to being correlated, WSOC concentrations were in similar proportions to anthropogenic tracers in both regions, despite biogenic volatile organic compounds (VOCs) that were on average 10-100 times higher over northern Georgia. In contrast, radiocarbon analysis on WSOC extracted from integrated filters deployed in Atlanta suggests that roughly 70-80% of the carbon in summertime WSOC is modern. If both findings are valid, the combined results indicate that in northern Georgia, fine-particle WSOC was secondary and formed through a process that involves mainly modern biogenic VOCs but which is strongly linked to an anthropogenic component that may largely control the mass of SOA formed. Independent of the radiocarbon results, a strong association between SOA and anthropogenic sources has implications for control strategies in urban regions with large biogenic VOC emissions.