| Abstract | This study assessed the ambient PM and PAHs levels to quantify the contributing sources using receptor modeling and the results were evaluated using emission inventory (EI). Further, an integrated framework was developed to assess the emission reduction measures in order to prioritize the workable measures for the Phnom Penh city (PNH). First, this study conducted the emission characterizations of the diesel back-up generators that were commonly used in Cambodia, yet there were no emission factors (EF) and emission profiles available. A hood was constructed for this purpose and isokinetic sampling was done to collect the emissions of PM and PAHs from two diesel generators representing the most common types used in the commercial sector of PNH. The average EFs of PM was 1.05 to 2.03 g/kg of fuel burned, higher value is for smaller generator. The total PAHs EFs were from 1.03 to 2.0 mg/kg of fuel burned and the gas phase PAHs contributed 86% of the total. The carbonaceous composition (EC and OC) of emitted PM was from 0.8 to 1.4 g/kg. Other prominent components of PM included ten water-soluble ions (total of 8 – 14 mg/kg fuel) that was about 1% of the emitted PM. The total 30 elements contributed 0.43 – 1.02 mg/kg with Al, Zn, Fe, Cr, V were the most predominant elements. Gases EFs were 10 – 14 g/kg CO and 3.9 – 4.05 g/kg SO2, with the higher value for the smaller engine. NOx and CO2 had EF of 13 – 19 g/kg NOx and 2519 – 2600 g/kg CO2, respectively, but the lower values were for the larger engine The EFs and emission profiles obtained were used in the subsequent EI and receptor modeling in this study. Ambient air quality monitoring was done at the urban traffic (UT) and sub-urban residential site (SR) sites focusing on PM2.5 & PM10 (UT) and PM2.5 (SR) collected on filters that were used to analyze for black carbon (BC), ions, elements, and particle phase PAHs (PPAH). Simultaneously, the gas phase PAHs (GPAH) were sampled using a PUF-module attached to the PM samplers. The 24h sampling was conducted simultaneously at both sites over the period from Feb 2016 to Jan 2017, to cover both dry and wet season. Higher levels of the PM2.5 at UT with the annual average of 37±18µg/m3 as compared to that of 28±15 µg/m3 at SR. The PM2.5 levels at both sites had similar temporal pattern which was also similar to that obtained at the only site, upwind of PNH, run by the government office. The 24h PM2.5 levels at UT and SR were exceeding the Cambodia standard of 50 µg/m3 with a frequency of 22% and 6%, respectively. The annual PM10 levels at UT were 57±21 µg/m3. The chemical compositions in UT PM2.5 of BC, ions and elements were 3.5±0.93 µg/m3; 8.2±4.4 µg/m3 and element 4.1±1.2 µg/m3 while those for PM10 were 4.7±0.84 µg/m3, 12.1±5.5 µg/m3 and 6.6±1.6 µg/m3, respectively. The corresponding levels of the composition in PM2.5 at SR were 3.3±0.74 µg/m3, 4.08±2.9 µg/m3 and 1.9±0.82 µg/m3. Both PM mass and PM compositions varied significantly with season with remarkably higher concentrations in dry season. The 16 USEPA priority PAHs were analyzed which showed the dominance of GPAHs i.e. 98±16 ng/m3 for UT and 60±10 ng/m3 for SR as compared to the PPAHs of in PM2.5 of 35±24 ng/m3 at UT and 31±20 ng/m3 at SR. Majority PPAHs at UT were in PM2.5 with the levels in PM10 (43±22 ng/m3) were almost the same as in PM2.5. Higher levels of PAHs were found in dry season that followed the trend of PM but the seasonal variation of PAHs were not that significant as for PM. The reconstructed mass (RCM) for PM2.5 and PM10 showed the major mass groups of OM-biomass in all PM sizes and sites. The source apportionment by CMB models also showed the major contributions from mobile source or on-road traffic (16-49% for UT; 17-21% for SR) and biomass burning (21-24% for UT; 32-56% for SR) iv and substantial contribution from secondary inorganic particles of ammonium, sulfates, nitrates for which the sources of the precursors should be further identified. For PAHs, the diagnostic ratios showed that traffic and biomass burning. The source apportionment by CMB also confirmed major sources of traffic (69%) for PAHs at UT and biomass burning (21-34%) at SR. The EI results showed the total annual emissions in 2015 for PNH were 14 Gg SO2, 9 Gg NOx, 99 Gg CO, 30 Gg NMVOC, 3 Gg PM2.5, 4.1 Gg PM10, 0.42 Gg BC, 0.86 Gg OC, 1.4 Gg CH4, 4723 Gg CO2 and 8.3 t PAHs. Mobile source (on-road traffic) was the main source of air pollution in PNH for most of the pollutants: PM (73% PM2.5; 54% PM10), SO2 (51%), NOx (74%), NMVOC (96%), BC and OC (45-64%), CO (91%) and CO2 (89%). PAHs were mainly emitted from the domestic cooking (28%), mobile source (27%), Solid waste open burning (SWOB, 26%), and power generation source (16%). The combination of EI and receptor modeling results thus confirmed the major emissions source of PM levels in PNH being on-road traffic and biomass burning. The major contributors of PAHs were also on-road traffic and biomass burning. The biomass burning in PNH may include the biomass fuel used in cooking, open burning of rice straw in the suburban areas and SWOB. The on-road traffic fleet in PNH consisted of motorcycle, light and heavy-duty vehicles Hence, the emission reduction strategies should be developed for these major sources. A comprehensive framework for the integrated assessment approach for the prioritization of emission reduction measures has been proposed in this study. Such framework should integrate all possible air quality management components (source measurement, ambient air quality monitoring, EI, receptor modeling and dispersion modeling) to identify and analyze the effectiveness of various emission reduction strategies for PNH taking into account the cost and benefit dimension, including the health benefits of the emission reduction. This study is a first comprehensive study on PM and PAH air pollution in Cambodia. The framework developed in this study is the first integrated framework for the country which may be useful for other developing countries in Asia and beyond. Further study should focus on dispersion modeling to analyze the emission control strategies (scenarios) in conjunction with the health and other benefits to provide science-based solutions to air quality management in Cambodia. |