In Korea, PM (Particulate Matter) emissions caused by coal-fired power plants are measured by a system, so called Clean Air Policy Support System (CAPSS), which uses foreign emission factors. However, the system fails to reflect the characteristics of domestic power plants. In this regard, this study aims to develop local, accurate domestic emission factors. The study measured the amount of TSP (Total Suspended Particulates), PM10 and PM2.5 by collecting samples from the latter parts of pollution control devices which were installed at 3 bituminous-fired power plants and 3 anthracite-fired power plants.The results showed that the average concentrations of TSP, PM10 and PM2.5 measured at bituminous-fired power plants were 4 , respectively). In addition, bituminous-fired power plants showed higher ratios of PM10/TSP and PM2.5/TSP with 0.66 and 0.92, respectively, compared to 0.82 and 0.46, the ratios of PM10/TSP and PM2.5/TSP measured in anthracite-fired power plants. Emission factors based-on concentration measurements were also higher for bituminous-fired power plants, and PM with smaller particles tended to have bigger difference in emission factors between the two fuels.This study calculated the amount of PM emissions by using the estimated emission factors. When it comes to the PM emissions, it was less than that of CAPSS while similar to that of CleanSYS in its amount. It is expected that the emission factors developed by this study will be used in Korea replacing foreign emission factors currently used in Korea by ensuring the objectivity and reliability as domestic emission factors.

It is very important to investigate air pollutants and emissions emitted from open burning in order to control nonpoint sources effectively. In this study, we utilized incineration simulator proposed by U.S. EPA and investigated concentrations of TSP, PM10, PM2.5 from woods and household wastes burning to calculate emission factors and build emission inventories.The results of experiment with 15 kg of woods and 3 kg of household wastes using the incineration simulator were as follows: in case of woods burning, TSP concentration was 66.4 mg/m 3 , PM10 concentration was 28.4 mg/m 3 , PM2.5 concentration was 17.9 mg/m 3 , respectively; in case of household wastes burning, TSP concentration was 118.4 mg/m 3 , PM10 concentration was 66.8 mg/m 3 , PM2.5 concentration was 55.2 mg/m 3 , respectively. Concentrations from household burning, as stated above, were higher than those from woods burning.Emission factors (EFs) for woods and household wastes burning were calculated as 2.45 and 6.75 g/kg for TSP, 0.86 and 5.45 g/kg for PM10, 0.78 and 4.81 g/kg for PM2.5, respectively. EFs of TSP, PM10, PM2.5 calculated from household wastes burning were higher than those of woods burning.When we added PM emissions from woods burning and household wastes burning to Korean National Emission Inventory named as Clean Air Policy Support System (CAPSS), CAPSS annual emissions of TSP, PM10, PM2.5 were increased by 0.08~0.26% (An increase rate for TSP, PM10, PM2.5 were 0.08~0.10%, 0.16~0.20% and 0.18~0.26%, respectively). Note that we assumed that the 1% of household wastes is emitted by open burning.

It is very important to investigate air pollutants emissions emitted from open burning in order to control nonpoint sources effectively. In this study, we utilized incineration simulator proposed by U.S EPA and investigated emissions of CO, OC/EC, from household waste and biomass burning to estimate pollutant emissions by illegal incineration of biomass wastes.Emission factor of OC was estimated as 17.1 g/kg for rice strew, 23.5 g/kg for barley, 10.3 g/kg for corn stover, 4.3 g/kg for unseasoned wood, respectively. In case of EC, it was calculated as 1.6 g/kg for rice strew, 4.3 g/kg for barley, 1.4 g/kg for corn stover, 0.6 g/kg for unseasoned wood, respectively.Most of the pollutants emissions were emitted at the stage 1 and 2. In the stage 3, the pollutants concentration decreased gradually.To estimate emissions and build inventory for biomass burning, we need to know accurate activity data. We, therefore, used activity data of both survey results of previous study and statistical data of National Statistical Office. However, we need to perform additional experiments in the future to obtain more accurate activity data for various cases.

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