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Abstract: Numerous reports have shown that fine particulates threaten human health. Since their health impact is associated with both mass and number concentrations, it is necessary to evaluate the emission standards for particulate mass accordingly. This study examined the particulate matter characteristics of diesel locomotive engine exhaust at various engine ratings. Diesel engine exhaust was collected via a dilution tunnel and the concentration and size distribution of fine particles were measured by a scanning mobility particle sizer. Exhaust gasses were measured simultaneously by a stack sampler. The maximum carbon monoxide emission was reached at 59% of the maximum rating, after which emissions decreased. The particle count median diameter increased with the engine rating, until a maximum was reached at 40% of the maximum rating. Most exhaust particles were nanoparticles with the nuclei mode range, a particle diameter (DP)<50nm. The increase in particles with the accumulation mode range, 50

Abstract: Monitoring the air quality in subway passenger cabins is important because of the large number of passengers and potentially high levels of air pollution. This report characterized PM10 levels in subway cabins in Seoul, Korea, and identified PM10 sources using elemental analysis and receptor modeling. PM10 levels in subway cabins were continuously measured using a light scattering monitor during rush and non-rush hours. A total of 41 measurements were taken during rush and non-rush hours, and the measurements were repeated in all four seasons. Filter samples were also collected for elemental composition analysis. Major PM10 sources were identified using positive matrix factorization (PMF). The in-cabin PM10 concentrations were the highest in the winter at 152.8 μg m−3 during rush hours and 90.2 μg m−3 during non-rush hours. While PM10 levels were higher during rush hours than during non-rush hours in three seasons (excluding summer), these levels were not associated with number of passenger. Elemental analysis showed that the PM10 was composed of 52.5% inorganic elements, 10.2% anions, and 37.3% other. Fe was the most abundant element and significantly correlated (p < 0.01) with Mn (r = 0.97), Ti (r = 0.91), Cr (r = 0.88), Ni (r = 0.89), and Cu (r = 0.88). Fe, Mn, Cr, and Cu are indicators of railroad-related PM10 sources. The PM10 sources characterized by PMF were soil and road dust sources (27.2%), railroad-related sources (47.6%), secondary nitrate sources (16.2%), and a chlorine factor mixed with a secondary sulfate source (9.1%). Overall, railroad-related sources contributed the most PM10 to subway cabin air. [Copyright &y& Elsevier]

Abstract: A measurement method combining multi-axis differential optical absorption spectroscopy (MAX-DOAS) and a transmissometer (TX) is introduced as a means of retrieving surface trace gas mixing ratios in ambient air. The combined measurement method was utilized to derive surface NO2 mixing ratios from 27 March to 11 May 2007 in Seoul, Korea. To convert the differential slant column density (DSCD) to the volume mixing ratio (VMR), the light path length (LPL) along the MAX-DOAS line of sight was derived using the light extinction coefficient and Ångstrom exponent data obtained by a TX and sunphotometer, respectively. Temporal variations of the NO2 VMRs at the 0–1km layer obtained from radiative transfer model (RTM) simulations coupled with MAX-DOAS data show similar patterns, but with reduced magnitudes, to the ground level data and those of the combined MAX-DOAS and TX measurements at 0.08km. The NO2 VMRs retrieved by the combined measurement were in agreement with those obtained from the RTM simulations coupled with MAX-DOAS data and the in-situ measurements within 40 and 50%, respectively. The coefficient of determination (R 2) of 0.75 was obtained between the combined measurement data sets and those of the RTM simulations coupled with MAX-DOAS data whereas that between the combined measurement data sets and those of the in-situ measurements was 0.53. The coefficient of determination (R 2) between the data sets derived from the RTM simulations coupled with MAX-DOAS data and those of the in-situ measurements was 0.67 with the scatter of the correlation within the 50% range. [Copyright &y& Elsevier]