Korean National Emissions Inventory System and 2007 Air Pollutant Emissions

Lee, Dae-Gyun; Lee, Yong-Mi; Jang, Kee-Won; Yoo, Chul Gyu; Kang, Kyoung-Hee; Lee, Ju‐Hyoung; Jung, Sungwoon; Park, Jung-Min; Lee, Sang-Bo; Han, Jong-Soo; Hong, Ji-Hyung; Lee, Suk-Jo

doi:10.5572/ajae.2011.5.4.278

Cited by 121 publications

(80 citation statements)

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“…The Clean Air Policy Support System (CAPSS) is a Korean emissions inventory system which provides annual air pollutant emissions with a spatial resolution of 1 km in South Korea as described by Lee et al (2011). For CAPSS, point source emissions are derived from both emission factors and activity data.…”

Section: Capssmentioning

confidence: 99%

“…updated the REAS inventory to a higher spatial and temporal resolution. Lee et al (2011) built the first version of the South Korean national emission inventory CAPSS (Clean Air Policy Support System) using more detailed local information for emission activities and factors. Tsinghua University developed the Chinese inventory MEIC (Multiresolution Emission Inventory for China) based on earlier work of Zhang et al (2009) (http://www.meicmodel.org).…”

Section: Introductionmentioning

confidence: 99%

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Intercomparison of NOx emission inventories over East Asia

Ding

Miyazaki

et al. 2017

Atmos. Chem. Phys.

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Abstract. We compare nine emission inventories of nitrogen oxides including four satellite-derived NO x inventories and the following bottom-up inventories for East Asia: REAS (Regional Emission inventory in ASia), MEIC (Multiresolution Emission Inventory for China), CAPSS (Clean Air Policy Support System) and EDGAR (Emissions Database for Global Atmospheric Research). Two of the satellitederived inventories are estimated by using the DECSO (Daily Emission derived Constrained by Satellite Observations) algorithm, which is based on an extended Kalman filter applied to observations from OMI or from GOME-2. The other two are derived with the EnKF algorithm, which is based on an ensemble Kalman filter applied to observations of multiple species using either the chemical transport model CHASER and MIROC-chem. The temporal behaviour and spatial distribution of the inventories are compared on a national and regional scale. A distinction is also made between urban and rural areas. The intercomparison of all inventories shows good agreement in total NO x emissions over mainland China, especially for trends, with an average bias of about 20 % for yearly emissions. All the inventories show the typical emission reduction of 10 % during the Chinese New Year and a peak in December. Satellite-derived approaches using OMI show a summer peak due to strong emissions from soil and biomass burning in this season. Biases in NO x emissions and uncertainties in temporal variability increase quickly when the spatial scale decreases. The analyses of the differences show the importance of using observations from multiple instruments and a high spatial resolution model for the satellite-derived inventories, while for bottom-up inventories, accurate emission factors and activity information are required. The advantage of the satellite-derived approach is that the emissions are soon available after observation, while the strength of the bottom-up inventories is that they include detailed information of emissions for each source category.

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Section: Capssmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Intercomparison of NOx emission inventories over East Asia

Ding

Miyazaki

et al. 2017

Atmos. Chem. Phys.

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“…The upperlevel categories include combustion in energy industries (point), non-industrial combustion plants (point and area), combustion in manufacturing industries (point and area), production processes (point and area), storage and distribution of fuels (point and area), solvent use (mobile), other mobile sources and machinery (mobile), waste treatment and disposal (point), agriculture (area), other sources and sinks (area), and fugitive dust (mobile and area). CO, NO x , SO x , PM 10 , and VOC emissions are provided for each upper-level category except for fugitive dust emissions (Lee et al, 2011).…”

Section: Capss 2007 and 2010mentioning

confidence: 99%

Regional contributions to particulate matter concentration in the Seoul metropolitan area, South Korea: seasonal variation and sensitivity to meteorology and emissions inventory

et al. 2017

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Abstract. The impact of regional emissions (e.g., domestic and international) on surface particulate matter (PM) concentrations in the Seoul metropolitan area (SMA), South Korea, and its sensitivities to meteorology and emissions inventories are quantitatively estimated for 2014 using regional air quality modeling systems. Located on the downwind side of strong sources of anthropogenic emissions, South Korea bears the full impact of the regional transport of pollutants and their precursors. However, the impact of foreign emissions sources has not yet been fully documented. We utilized two regional air quality simulation systems: (1) a Weather Research and Forecasting and Community Multi-Scale Air Quality (CMAQ) system and (2) a United Kingdom Met Office Unified Model and CMAQ system. The following combinations of emissions inventories are used: the Intercontinental Chemical Transport Experiment-Phase B, the Intercomparison Study for Asia 2010, and the National Institute of Environment Research Clean Air Policy Support System. Partial contributions of domestic and foreign emissions are estimated using a brute force approach, adjusting South Korean emissions to 50 %. Results show that foreign emissions contributed ∼ 60 % of SMA surface PM concentration in 2014. Estimated contributions display clear seasonal variation, with foreign emissions having a higher impact during the cold season (fall to spring), reaching ∼ 70 % in March, and making lower contributions in the summer, ∼ 45 % in September. We also found that simulated surface PM concentration is sensitive to meteorology, but estimated contributions are mostly consistent. Regional contributions are also found to be sensitive to the choice of emissions inventories.

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“…As for anthropogenic emissions, the Intercontinental Chemical Transport Experiment-Phase B (INTEX-B) inventory for the year 2006 (Zhang et al, 2009;Li et al, 2014) was used for Northeast Asia, while the Clean Air Policy Support System (CAPSS) inventory for the year 2007 was used for Korea (Kim et al, 2008;Lee et al, 2011). Raw emission data were processed to generate gridded, hourly emission fields using the Sparse Matrix Operator Kernel Emissions Processor (SMOKE) v2.1 (http://www.smokemodel.org).…”

Section: Modelingmentioning

confidence: 99%

Evaluation of Model Performance for Forecasting Fine Particle Concentrations in Korea

Ghim

Choi

Kim

et al. 2017

Aerosol Air Qual. Res.

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The performance of a modeling system consisting of WRF model v3.4.1 and CMAQ model v4.7.1 for forecasting fine particle concentrations were evaluated using measurement data at the surface. Twenty-four hour averages of PM 2.5 and its major components at Bulgwang (located in the northwest of Seoul) during the period February 2012 through January 2013 were compared with predicted concentrations as well as hourly averages of inorganic ions measured at Yongin (located to the southeast of Seoul) in spring 2012. The mean fractional bias (MFB) of -0.37 for PM 2.5 at Bulgwang fell just outside the goal of -0.3, the level of accuracy that the best model can be achieved. Negative values of MFB, especially in winter, along with the correlation coefficient of 0.61 between measured and predicted concentrations showed that the model performance at Bulgwang was closer to that for Europe than that for North America. However, underestimation of SO 4 2-and overestimation of NO 3 -were similarly observed at Bulgwang as in the United States. Although diurnal variations in the measured values showed distinctive features at Yongin according to the classified patterns, most variations in the predicted values typically showed a peak early in the morning followed by an increase at night.

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Korean National Emissions Inventory System and 2007 Air Pollutant Emissions

Cited by 121 publications

References 1 publication

Intercomparison of NO<sub><i>x</i></sub> emission inventories over East Asia

Intercomparison of NO<sub><i>x</i></sub> emission inventories over East Asia

Regional contributions to particulate matter concentration in the Seoul metropolitan area, South Korea: seasonal variation and sensitivity to meteorology and emissions inventory

Evaluation of Model Performance for Forecasting Fine Particle Concentrations in Korea

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Korean National Emissions Inventory System and 2007 Air Pollutant Emissions

Cited by 121 publications

References 1 publication

Intercomparison of NO&lt;sub&gt;&lt;i&gt;x&lt;/i&gt;&lt;/sub&gt; emission inventories over East Asia

Intercomparison of NO&lt;sub&gt;&lt;i&gt;x&lt;/i&gt;&lt;/sub&gt; emission inventories over East Asia

Regional contributions to particulate matter concentration in the Seoul metropolitan area, South Korea: seasonal variation and sensitivity to meteorology and emissions inventory

Evaluation of Model Performance for Forecasting Fine Particle Concentrations in Korea

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Product

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Intercomparison of NO<sub><i>x</i></sub> emission inventories over East Asia

Intercomparison of NO<sub><i>x</i></sub> emission inventories over East Asia