• Journal of Korean Society for Atmospheric Environment
• /
• v.26 no.3
• /
• pp.276-285
• /
• 2010

Recently the Korean government has tried to cut down the $PM_{10}$ concentration by the Special Law for Air Quality Improvement. But the concentrations of $PM_{10}$ have exceeded the air quality standard at most monitoring stations. Primary $PM_{10}$ emitted from various sources and emission data have large uncertainty. The biomass burning is one of the major sources of $PM_{10}$ emission. The biomass burning is composed of wood stove usage, meat cooking and agricultural combustion etc.. Activity data and emission factors for the biomass burning are limited, and it is hard to calculate the air pollution emissions from these sources. In this study, we tried to estimate the air pollution emission from residential wood stove usage. The number of total wood stoves is estimated by the survey of wood stove manufacturer. And air pollution emission factors for the wood stove are investigated using the flue gas measurement by U.S. EPA particulate test method (Method 5G). As the results, the $PM_{10}$ and CO emission factors of wood stove are estimated as 7.7 g/kg-wood and 78.8 g/kg-wood respectively. The annual $PM_{10}$ and CO emissions from wood stove are calculated as 1,200~3,600 ton/year and 12,600~36,400 ton/year in Korea. It is confirmed that wood stove is the one of major sources of biomass burning, and the survey for activity data and the measurement for emission factors are needed for reducing the uncertainty of these emission data.

• Journal of Korean Society for Atmospheric Environment
• /
• v.31 no.4
• /
• pp.319-329
• /
• 2015

The characteristics of aerosol light extinction were investigated by comparing measured and calculated extinction coefficient to understand the contribution of air pollutants on visibility impairment for data during 4 months (Jan~ April), 2014. The integrated nephelometer and aethalometer system were installed to measure the scattering and absorption coefficients of aerosol as well as BAM 1020, MARGA, semi-continuous OCEC analyzer, and online-XRF to calculate the extinction coefficient. The IMPROVE_2005 equation was used to determine the contributions of different chemical components on visibility impairment in $PM_{2.5}$ and $PM_{10}$ due to highest correlation with measured data. Sulfate, nitrate, and organic mass by carbon (OMC) of fine aerosol were the major contributors affecting on visibility impairment. Total contributions to light extinction were calculated as $631.0Mm^{-1}$ for the worst-case and $64.4Mm^{-1}$ for the best-case. The concentrations of aerosol component for the worst-case were 38.4 times and 45.5 times larger than those of the best-case for $(NH_4)_2SO_4$ and $NH_4NO_3$, respectively. At lower visibility condition, in which extinction coefficient was higher than $400Mm^{-1}$, extinction coefficient varied according to the relative humidity variation regardless of $PM_{2.5}$.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.19 no.4
• /
• pp.118-129
• /
• 2016

Many epidemiological studies, relying on administrative air pollution monitoring data, have reported the association between particulate matter ($PM_{10}$) air pollution and human health. These monitoring data were collected at a limited number of fixed sites, whereas government-generated health data are aggregated at the area level. To link these two data types for assessing health effects, it is necessary to estimate area-level concentrations of $PM_{10}$. In this study, we estimated district (Gu)-level $PM_{10}$ concentrations using a previously developed pointwise exposure prediction model for $PM_{10}$ and three types of point locations in Seoul, Korea. These points included 16,230 centroids of the largest census output residential areas, 422 community service centers, and 610 centroids on the 1km grid. After creating three types of points, we predicted $PM_{10}$ annual average concentrations at all locations and calculated Gu averages of predicted $PM_{10}$ concentrations as representative Gu-estimates. Then, we compared estimates to each other and to measurements. Prediction-based Gu-level estimates showed higher correlations with measurement-based estimates as prediction locations became more population representative ($R^2=0.06-0.59$). Among the three estimates, grid-based estimates gave lowest correlations compared to the other two(0.35-0.47). This study provides an approach for estimating area-level air pollution concentrations and assesses air pollution health effects using national-scale administrative health data.

• Proceedings of the Korea Air Pollution Research Association Conference
• /
• 2008.10a
• /
• pp.363-364
• /
• 2008

• Proceedings of the Korea Air Pollution Research Association Conference
• /
• 2008.04a
• /
• pp.506-507
• /
• 2008

• Asian Journal of Atmospheric Environment
• /
• v.7 no.4
• /
• pp.177-190
• /
• 2013

Air pollution trends in Japan between 1970 and 2012 were analyzed, and the impact of air pollution countermeasures was evaluated. Concentrations of CO decreased from 1970 to 2012, and in 2012, the Japanese environmental quality standard (EQS) for CO was satisfied. Concentrations of $SO_2$ dropped markedly in the 1970s, owing to use of desulfurization technologies and low-sulfur heavy oil. Major reductions in the sulfur content of diesel fuel in the 1990s resulted in further decreases of $SO_2$ levels. In 2012, the EQS for $SO_2$ was satisfied at most air quality monitoring stations. Concentrations of $NO_2$ decreased from 1970 to 1985, but increased from 1985 to 1995. After 1995, $NO_2$ concentrations decreased, especially after 2006. In 2012, the EQS for $NO_2$ was satisfied at most air quality monitoring stations, except those alongside roads. The annual mean for the daily maximum concentrations of photochemical oxidants (OX) increased from 1980 to 2010, but after 2006, the $98^{th}$ percentile values of the OX concentrations decreased. In 2012, the EQS for OX was not satisfied at most air quality monitoring stations. Non-methane hydrocarbon (NMHC) concentrations generally decreased from 1976 to 2012. In 2011, NMHC concentrations near roads and in the general environment were nearly the same. The concentration of suspended particulate matter (SPM) generally decreased. In 2011, the EQS for SPM was satisfied at 69.2% of ambient air monitoring stations, and 72.9% of roadside air-monitoring stations. Impacts from mineral dust from continental Asia were especially pronounced in the western part of Japan in spring, and year-round variation was large. The concentration of $PM_{2.5}$ generally decreased, but the EQS for $PM_{2.5}$ is still not satisfied. The air pollution trends were closely synchronized with promulgation of regulations designed to limit pollutant emissions. Trans-boundary OX and $PM_{2.5}$ has become a big issue which contains global warming chemical species such as ozone and black carbon (so called SLCP: Short Lived Climate Pollutants). Cobeneficial reduction approach for these pollutants will be important to improve both in regional and global atmospheric environmental conditions.

• Journal of Korean Society for Atmospheric Environment
• /
• v.25 no.5
• /
• pp.410-419
• /
• 2009

Generally, air pollutant emission at workplace is estimated by two methods: indirect methods using emission factors and direct methods based on CEMS (Continuous Emission Monitoring System). CAPSS (Clean Air Policy Support System) is a representative indirect method and the national air pollutant database of Korea. However, characteristics of some workplaces may create a gap between CAPSS and CEMS data. For improving of emission data accuracy, emission data of CEMS (named CleanSYS) equipped at 138 target workplaces were compared with those of CAPSS. As a result, $SO_x$ and $PM_{10}$ emission levels obtained by CAPSS were lower than those of CleanSYS. $SO_x$ and $PM_{10}$emission ratios were 61.5% and 71.2% lower respectively, showing the biggest gaps. On the other hand, $NO_x$ emission of CAPSS was higher by 10.4%. $SO_x$ showed the biggest difference in 'Energy industry combustion' and $NO_x$ did in 'Production Process' within the SCC category. $PM_{10}$ presented a large gap in 'Manufacturing industry combustion.' The differences in $SO_x$ between the two systems occurred because some large-size facilities lack pollution controllers or efficient pollution controllers. Based on this study, CAPSS emission database of Korea will improve accuracy through adopting CEMS emission system, which enables more efficient national atmospheric policies and workplace management.

• Asian Journal of Atmospheric Environment
• /
• v.11 no.4
• /
• pp.254-269
• /
• 2017

The work describes an assessment of the major air pollutants, $NO_2$, $SO_2$, CO, $O_3$, $NH_3$, coarse and fine particulate matter ($PM_{10}$, $PM_{2.5}$) in ambient air in and around a 3 million tonne Petroleum Refinery and the possible impacts on a pristine area marked by the presence of the world-famous Kajiranga National Park, a world heritage site and habitat for the most number of one-horned rhinos in the world. The Refinery is at an aerial distance of 20-25 km from the wildlife habitat. The assessment is based on regular monitoring at four stations around the Refinery and one station near the National Park. Heavy rains during June to August influence the pollutant concentrations while at other times of the year, large traffic volume adds to the pollutant concentrations that peak during November to March, the dry months of the year. Correlation analysis by scatter technique is utilised to obtain the enhancement ratios to predict the variations in the concentrations of the pollutants and their spatial distribution. Computation of air quality index (AQI) indicates that the coarse and the fine particulates in the ambient air could be a major hazard to wildlife in the area.

• Proceedings of the KSRS Conference
• /
• 2005.10a
• /
• pp.378-380
• /
• 2005

Remote sensing of atmospheric aerosol using MODIS satellite data has been proven to be very useful in global/regional scale aerosol monitoring. Due to their large spatial resolution of $10km^2$ MODIS aerosol optical thickness (AOT) data have limitations for local/urban scale aerosol monitoring applications. Modified Bremen Aerosol Retrieval (BAER) algorithm developed by von Hoyningen-Huene et al. (2003) and Lee et al. (2005) has been applied in this study to retrieve AOT in fe resolutions of $500m^2$ over Korea. Look up tables (LUTs) were constructed from the aerosol properties based on sun-photometer observation and radiation transfer model calculations. It was found that relative error between the satellite products and the ground observations was within about $15\%$. Resulting AOT products were correlated with surface PMIO concentration data. There was good correlation between MODIS AOT and surface PM concentration under certain atmospheric conditions, which supports the feasibility of using the high-resolution MODIS AOT for local and urban scale air quality monitoring

• Particle and aerosol research
• /
• v.8 no.4
• /
• pp.151-160
• /
• 2012

Health effects caused by the ultrafine particles in ambient air are great concern to the public health, and the strict measuring and monitoring of the ambient aerosol are required. In this work, the characteristics of the aerosol size distribution in Pohang province are studied. Optical particle counters (Grimm APS 1108 and 1109) were used to measure the aerosol size distribution in the area. Locations near the national monitoring site located in the industrial and the residence area were selected for the measuring sites of this study, and the locations in border area between the industry and the residence were selected for the reference of the comparison. In the industry site, it is found that the concentration of aerosol particles near the size of 5 ${\mu}m$ appear characteristically and the fluctuations in concentration with respect to time are minimal. The mass concentration of the aerosol above 10 ${\mu}m$ in diameter in the industry area was found to fluctuate significantly. The mass portion of $PM_{10}$ and PM2.5 to TSP in the residence area were 83% and 51% respectively. In the industrial regional, it was found that the mass portion of PM10 and $PM_{2.5}$ to TSP were 76% and 35% respectively. In the boundary area the mass portion of $PM_{10}$ and $PM_{2.5}$ to TSP were 78% and 54% respectively.