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The aims of this study were to examine the removal of bacteria and viruses by household point-of-use (POU) treatments and to apply a previously developed large-volume virus concentration method (∼20 L). First, the removal of microbes by household POU treatment was investigated in the laboratory. Second, the prevalence of viruses in drinking water sources for households and the removal efficiency of microbes by POU treatments in two suburban communities in Hanoi, Vietnam, were investigated. Indigenous pepper mild mottle virus (PMMoV) was used as the main target together with adenovirus, Aichi virus, enterovirus, F-specific bacteriophage genogroup 1, andEscherichia colito investigate the removal efficiency of household treatments. The results from laboratory and field survey were compared. From the laboratory study, ceramic membranes were not effective for removing viruses and bacteria from water; pathogen reduction was less than 1.5 log10. By contrast, reverse osmosis (RO) devices reduced microbes by 3 to > 5 log10. In a field study, PMMoV was found to be the most prevalent waterborne virus. Household sand filtration was ineffective for removingE. coli, total coliforms and PMMoV; the reduction was less than 1 order of magnitude. Boiling the water and then filtering it with a ceramic membrane reducedE. coliby 3 orders of magnitude, but this was not effective for removing PMMoV. RO filtration was one of the promising methods for removingE. coli, total coliforms and PMMoV to below their detection limits in most of the samples studied. The removal ofE. coli, total coliforms and PMMoV was >2.3, >4 and >3 log10, respectively. The laboratory results of virus removal efficiency by POU devices agreed with the field study. Due to the prevalence and characteristics of PMMoV, it is a strong candidate for an indigenous indicator to investigate the viral removal efficiency of household POU treatments. [ABSTRACT FROM AUTHOR]

This study was aimed at investigating source apportionment of PAHs in urban road dust. Seven kinds of PAHs sources were defined: diesel vehicle exhaust, gasoline vehicle exhaust, tire, asphalt-pavement, asphalt or bitumen, petroleum products excluding tire and asphalt, and the combustion products except for those in vehicle engines. Using cluster analysis combined with principal component analysis, 189 source data were classified into 11 source groups (S1–S11) based on the content percentage of 12 individual PAHs (12-PAH profiles). Thirty-seven dust samples on nine streets in Tokyo were collected and analyzed for 12-PAH profiles. In order to estimate the PAHs, contributions of S1–S11 to dust samples, the multiple regression analysis was performed. The 12-PAH profiles of each dust sample and those of 11 source groups were applied as dependent and independent variables, respectively. We defined the comparative contribution of each source group as the ratio of each regression coefficient to the sum of them. The result revealed that diesel vehicle exhaust, tire, and pavement were the major contributors of PAHs in the road dust. [ABSTRACT FROM AUTHOR]