Exposure Modeling of Benzene Exploiting Passive–Active Sampling Data

摘要: The objective of the present study is exploitation active sampling personal exposure data in assessing factors that affect to benzene combination with widely accepted scheme passive sampling—time microenvironment–activity diaries (TMAD). campaign included measurements both and several microenvironments, evaluation TMAD kept by volunteers, a variety environmental (ambient air determination, traffic meteorological observations). Due relatively elevated emissions, average was determined be equal 8.9 μg/m3, ranging between 5 20 which value highly related urban concentration (9.2 μg/m3). information gained from embedded (in terms spatial temporal distribution) into three zones respectively, order draw statistically significant conclusions about levels activity patterns. contribution activities overall amount further quantified refined measurements. These revealed driving traffic-congested road main leading (up 70 μg/m3), followed walking on roadside congested 35 Indoor general lower than outdoor (indicating dominant source emissions wider area), it significantly affected presence tobacco smoke. higher significance regression coefficients obtained statistical analysis fundamental for development regression-based prediction model. model evaluated through comparison data, were considered as an unknown but realistic pattern. performed very well expressing variance score R2 0.935. All above indicate necessary albeit more laborious tool needs used complement precise quantification determining