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Verification of NOx emission inventories over North Korea
Environmental Pollution 195 (2014) 236e244
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Environmental Pollution journal homepage: www.elsevier.com/locate/envpol
Verification of NOx emission inventories over North Korea Na Kyung Kim a, Yong Pyo Kim a, *, Yu Morino b, Jun-ichi Kurokawa c, Toshimasa Ohara b, * a
Department of Environmental Science and Engineering, Ewha Womans University, Seoul, Republic of Korea National Institute for Environmental Studies, Tsukuba, Ibaraki, Japan c Atmospheric Research Department, Asia Center for Air Pollution Research, Niigata, Japan b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 13 March 2014 Received in revised form 24 June 2014 Accepted 28 June 2014 Available online 26 July 2014
In this study, the top-down NOx emissions estimated from satellite observations of NO2 vertical column densities over North Korea from 1996 to 2009 were analyzed. Also, a bottom-up NOx emission inventory from REAS 1.1 from 1980 to 2005 was analyzed with several statistics. REAS 1.1 was in good agreement with the top-down approach for both trend and amount. The characteristics of NOx emissions in North Korea were quite different from other developed countries including South Korea. In North Korea, emissions from industry sector was the highest followed by transportation sector in the 1980s. However, after 1990, the NOx emissions from other sector, mainly agriculture, became the 2nd highest. Also, no emission centers such as urban areas or industrial areas were distinctively observed. Finally, the monthly NOx emissions were high during the warm season. © 2014 Elsevier Ltd. All rights reserved.
Keywords: North Korea NOx emission inventories REAS 1.1 Top down NOx estimation
1. Introduction NOx is a major air pollutant in Northeast Asia including China, South and North Korea and Japan, and the emission of NOx in the region is drastically increasing (see, for example, Zhang et al., 2009). NOx is emitted from anthropogenic sources such as fossil fuel combustion and biomass burning, as well as natural sources such as lightning and microbiological processes in soil and plays important roles in oxidation processes in the atmosphere. Several studies on NOx emissions have been carried out to find out their influence on the air quality in Northeast Asia (Uno et al., 2007; Wang et al., 2007; Zhang et al., 2007). Recently, several studies using satellite measurements reported that NO2 vertical column density have increased significantly in East Asia (Richter et al., 2005; He et al., 2007). North Korea is also located in Northeast Asia (Fig. 1), but the studies about the emissions of air pollutants or air quality in North Korea are rare due to its closed characteristics to the outside world. In general, emission inventories are made by the bottom-up approach, which is based on the combinations of activity statistics (such as energy consumption and industrial production) and source-or region-specific emission factors (Ohara et al., 2007; Kurokawa et al., 2009a). However, North Korea publishes few statistics on its energy sector or other economic activities (UNEP, 2003, 2012), and few quantitative estimates describing activities in the
* Corresponding authors. E-mail addresses: [email protected] (Y.P. Kim), [email protected] (T. Ohara). http://dx.doi.org/10.1016/j.envpol.2014.06.034 0269-7491/© 2014 Elsevier Ltd. All rights reserved.
North Korean energy sector made by outside groups tend to be uneven in quality (Hayes et al., 2011). Consequently, the emission inventories of North Korea are very rare and and contain large uncertainty. Kim et al. (2011) reviewed the characteristics of energy consumption, emissions of air pollutants, and ambient air quality in North Korea. Kim I.S. et al. (2013) identified the characteristics of energy consumption in North Korea as (1) very low energy consumption per capita, (2) high dependence on coal and biofuel, and (3) low level of combustion and control technologies. Further, they combined the Chemical Mass balance Model (CMB) result for the particulate Polycyclic Aromatic Hydrocarbons (PAHs) data in Seoul and backward trajectory analysis result and estimated that at least 20% of the particulate PAHs observed in winter in Seoul were from North Korea (Kim I.S. et al., 2013). However, without reliable emission inventory data for North Korea, it is hard to validate these study results. In this case, “top-down” or inverse modeling approaches, in which emissions are optimized in order to reduce the differences between the simulated and observed data, is a powerful method that alleviates the problems of the bottom-up approach and estimate the emissions of air pollutants (Kurokawa et al., 2009a). For example, Kim N.K. et al. (2013) compared two bottom-up emission inventories, Clean Air Policy Support System (CAPSS) and Regional Emission inventory for ASia (REAS 1.1) and one top-down emission estimated from satellite observation on South Korea. They have shown that the top-down emission result is close to the CAPSS emission result. They also found that REAS 1.1 and the top-down emission showed the same
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Fig. 1. The map of North and South Korea.
trend while the absolute amounts were different by about 25%. They further identified that the difference was mainly caused by spatial distribution of emissions from transportation sector. They concluded that the top-down approach is a reliable one. To understand the characteristics of the emissions of NOx in North Korea, top-down NOx emissions estimated from satellite observations of NO2 vertical column densities over North Korea from 1996 to 2009 were analyzed, and compared with the REAS 1.1 emission inventory which includes the air pollutant emissions in North Korea from 1980 to 2005. Also these were compared with several statistics to find out the trend and characteristics. These results are compared with those in South Korea to clarify the characteristics of NOx emissions in North Korea. It is the first study to compare the bottom-up and the top-down emission inventories with various statistical data for North Korea, and therefore, it will be useful to understand the NOx emission in North Korea. 2. Data 2.1. Bottom-up emission inventory The bottom-up emission inventory analyzed in this study is Regional Emission inventory in ASia (REAS 1.1) developed by Ohara et al. (2007), which includes the air pollutant emission from North Korea. REAS 1.1 includes ten air pollutants, NOx, SO2, CO, Black Carbon (BC), Organic Carbon (OC), CO2, N2O, NH3, CH4, and Non-
Methane Volatile Organic Compounds (NMVOCs) from anthropogenic activities. The target domain of REAS 1.1 covers 24 countries in East, Southeast, and South Asia. Emissions were estimated on the basis of activity data at district levels for China (30 provinces), India (20 states), Japan (6 sub-regions), South Korea (4 sub-regions), and Pakistan (5 sub-regions). For other countries including North Korea, national emissions were estimated on the basis of activity data at the national level (Ohara et al., 2007). Emissions were estimated as a product of the activity data, emission factors, and removal efficiency of emission controls. Region-specific emission factors for subdivided source sectors were developed from a wide range of literature and were used to estimate emissions on district and country levels. These emissions, estimated on district and country levels, were divided into a 0.5 0.5 grid by using index databases, i.e. population data, information on the positions of large point sources (LPSs), land cover data sets, and land area data sets. Details on REAS 1.1 could be found in Ohara et al. (2007). In this study, the NOx emission inventory of REAS 1.1 from 1980 to 2003 (Ohara et al., 2007; http://www.jamstec.go.jp/frsgc/ research/d4/emission.htm) and extended data till 2005 (Kurokawa et al., 2009b) were analyzed. 2.2. Top-down NOx emission inventory Detailed description on the top-down NOx emission inventory was given in Kim N.K. et al. (2013). Briefly, a simple iteration
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grid cells is not fully reflected. So, in this study, relatively coarse horizontal resolution (80 km) is used in CMAQ. Note that in this methodology, NOx emissions were strongly forced to be adjusted by the differences of observed and simulated NO2 VCDs in each grid. So, influence of initial NOx emissions is expected to be small. Monthly averaged top-down NOx emissions in North Korea were estimated using this methodology from January 1996 to December 2009. 3. Results 3.1. Long term trend of the NOx emissions In Fig. 2, the total amounts of NOx emissions of North Korea from REAS 1.1 between 1980 and 2005 are shown, and compared to the total amounts of NOx emissions of South Korea from REAS 1.1 and CAPSS developed by National Institute of Environmental Research (NIER), South Korea (NIER, 2011). In the early 1980s, the total amounts of NOx emissions of North Korea were comparable to those of South Korea, however, the emissions decreased below 10e20% of South Korea after the 1990s due to poor economic conditions in North Korea (Kim et al., 2011; Kim I.S. et al., 2013). Kim I.S. et al. (2013) found that with the collapse of the former Soviet Union in 1989, the energy supply of North Korea, especially that of petroleum, has decreased drastically, reducing emissions of air pollutants. To figure out detailed economic conditions in North Korea, several statistics were investigated and shown in Fig. 3. The economic growth rates of North Korea were negative, about 5% from 1990 till 1997, and the Gross National Income (GNI) and total primary energy consumption kept decreasing until 1998 (Bank of Korea (2012)). After 1999, the economic growth rate became positive, but the economic situation in North Korea was still in poor condition, and the total energy consumption in North Korea kept low, below 2 million tonne of oil equivalent (TOE) per year. In Fig. 4, the energy structures of total primary energy consumption for North Korea between 1965 and 2009 were shown (Korean Statistical Information Service, 2011). During the whole period, coal was the main energy source in North Korea, and the proportions of coal use were more than 60%. However, the absolute amount of coal mining and, thus, consumption was decreased in the 1990s, and then did not change much because of antiquated mining instruments and the deepening of the coal mines. Furthermore, oil imports have not been affordable in current
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methodology was used to obtain monthly top-down NOx emissions with which chemical transport model (CTM) reproduces the satellite observation of monthly NO2 vertical column densities (VCDs). In this study, the three-dimensional regional-scale chemical transport modeling system developed jointly by Kyushu University and the National Institute for Environmental Studies (NIES) (Uno et al., 2007) was used. The Models-3 Community Multiscale Air Quality (CMAQ) modeling system (Byun and Schere, 2006) and the Regional Atmospheric Modeling System (RAMS) version 4.4 (Pielke et al., 1992) were adopted for the system. The horizontal model domain for the CMAQ simulation was 6240 km 5440 km on a rotated polar stereographic map projection centered at 25 N, 115 E, with a grid resolution of 80 km 80 km. For vertical resolution, the modeling system employed 14 grid points extending from the surface to 22 km with 14 stretching grid layers in the sigma-z coordinate system. The CMAQ full chemistry model requires the emission inventories not only for NOx but also other chemical species for input data. Anthropogenic emissions of all species were taken from REAS 1.1 (Ohara et al., 2007; See Section 2.1 for detail). For NOx emissions from soil sources, datasets were prepared based on monthly estimations for the year 2001 and annual emissions for the year 1990 by Yan et al. (2003a, b, 2005). Data for 2001 were adopted for the years after 2002. For the years before 2001, first, monthly emissions for 1990 were estimated assuming the same monthly variations as in 2001, and then emissions were linearly interpolated to each year. Biogenic emissions of isoprene and monoterpenes were taken from monthly estimations for the 1990s by Guenther et al. (1995), and emissions of all species from vegetation fires were taken from inventories for the late 1990's from Streets et al. (2003) and used for all the years. In this study, lightning NOx emission was not included because lightning NOx was considered to contribute little to NOx VCDs during daytime (Martin et al., 2002; Edwards et al., 2003). For satellite-derived NO2 VCDs, Global Ozone Monitoring Experiment (GOME) and Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) observation data are used. GOME was a passive remote sensing instrument on board the ERS-2 satellite launched in April 1995. It provided observed data with a resolution of 40 km (latitude) 320 km (longitude) until June 2003. The ERS-2 satellite crosses the equator at 1030 Local Time (LT) in a sun-synchronous polar orbit, and global coverage was archived every 3 days. The version 2 tropospheric NO2 VCDs data products retrieved by the University of Bremen were used in this study. Richter et al. (2005) indicate that a rough estimate of the GOME retrieval errors is an additive error of approximately 0.5e1.0 1015 molecules cm 2 and a relative error of 40e60% for monthly averages over polluted regions. Detailed description for GOME NO2 VCDs retrieval was provided by Richter and Burrows (2002) and Richter et al. (2005). SCHIAMACHY is also a passive remote sensing instrument observing backscattered, reflected, transmitted or emitted radiation from the atmosphere and surface of the Earth. SCHIAMACHY is on board Environmental Satellite (ENVISAT) which was launched in March 2002 and has a dayside equatorial crossing time of 1000 LT. Resolution of SCIAMACHY is 30 km (latitude) 60 km (longitude). SCIAMACHY tropospheric excess NO2 VCDs version 0.7 and 0.8 retrieved by the University of Bremen were used in this study. Richter et al. (2005) and van der A et al. (2006) have shown that the bias between GOME and SCHIAMACHY is smaller than the minimum error (0.5 1015 molecules cm 2) in the data, and therefore, the bias can be neglected. In this study, the retrievals of GOME from 1996 to 2002 and those of SCIAMACHY from 2003 to 2009 were used. In this methodology, the influence of NOx emissions on NO2 VCDs is adjusted only by the column just over the emission grid. It means that the influence of transport of NOx from the neighboring
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Fig. 2. NOx emission trends of North Korea from REAS and South Korea from CAPSS and REAS.
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Fig. 3. Ttrends of Gross National Income (GNI) (Bank of Korea (2012)), economic growth rate, and the total primary energy consumption of North Korea (Korean Statistical Information Service, 2011).
economic condition in North Korea. Therefore, the NOx emission in North Korea is projected to keep low for a while. 3.2. Comparison to other bottom- up and top-down estimated NOx emissions In Fig. 5, the NOx emissions in North Korea from REAS 1.1 and other bottom-up emission inventories are shown, and they are compared with the top-down estimated NOx emissions. Since uncertainties of the top-down estimated NOx emissions tend to be larger in wintertime due to relatively long lifetime of NOx, the top-down estimated NOx emission with and without winter were shown, respectively. The top-down estimated NOx emissions with winter includes the whole estimated result with the uncertainties in winter time. On the other hand, the top-down estimated NOx emissions without winter were calculated by applying factor of 1.5 to the top-down estimated NOx emissions only 8 months from March to October to exclude the uncertainties in wintertime.
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Fig. 4. Energy structures of total primary energy consumption of North Korea from 1965 to 2009 (Korean Statistical Information Service, 2011).
First of all, the top-down estimated NOx emissions were well matched to REAS 1.1 except for 2003 and 2005. Especially, the absolute values of top-down estimated NOx emission between 1996 and 2002 were quite close to REAS 1.1. Other bottom-up inventories were highly different from the top-down estimated NOx emissions. The NOx emission inventory from Jung et al. (1996) (see the right y-axis) was more than 10 times higher than the top-down estimated NOx emissions in 1994. The NOx emission inventory from Kwak and Cho (1999) was about 2 times higher than the top-down estimated NOx emissions in 2003. On the other hand, NOx emission inventories from Kim (2005) were much smaller than the top-down estimated NOx emissions. To sum it up, the top-down emission inventory matches better with REAS 1.1 than other available emission inventories, and therefore, REAS 1.1 seems to be the most reliable bottom-up NOx emission inventories for North Korea. The trend of the top-down result for the whole year and the top-down results without winter (March to October only) matched well, and the top-down estimated NOx without winter was higher than the top-down estimated NOx for the whole year. It is different from the trend shown for South Korea (Kim et al., 2013). It may suggest higher NOx emission in summer than winter in North Korea and it will be discussed in section 3.5. 3.3. Sectoral NOx emission trends Since REAS 1.1 emission inventory is in good agreement with the top-down approach result for both trend and absolute amount, further analysis is carried out on the REAS 1.1 data. In Fig. 6, sectoral NOx emission trends of North Korea between 1980 and 2005 from REAS 1.1 are shown. During the whole period, industry was the biggest source of NOx emission in North Korea, about a half of the total. However, its emission amount decreased almost half from the middle of the 1980s to the late 1990s. The main energy source of industry in North Korea has been coal which has been produced by the mining in North Korea, and as it was mentioned in section 3.1, the absolute amounts of coal mining kept decreasing. Therefore, the NOx emission from industry sector decreased consequently. The NOx emission from transportation sector was the 2nd highest in the 1980s (22% on the average), but it also kept decreasing. Since the mid-1990s, the NOx emissions from transformation and other sectors (mainly consisted by domestic and agriculture) became higher than transportation sector and, recently, it took 18% on the average.
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Fig. 5. Comparisons of the bottom-up and the top-down NOx emission data in North Korea. The right y-axis scale is used for the emission data of Jung et al. (1996).
domestic energy types in North Korea have been coal and biofuel. In North Korea, overall energy supply has been in poor condition, and therefore only NOx emissions from domestic energy use and agriculture barely keep certain values, and this trend affects the total NOx emissions in North Korea.
Contrastingly, in South Korea, the transportation sector has been the biggest source of NOx emissions, and its contribution to the total NOx emission is increasing (Kim N.K. et al., 2013). This trend is common not only in South Korea but also in other developed countries. Therefore, this trend is the characteristic of NOx emission in North Korea, and it is also explained by poor energy supply conditions in North Korea, especially, oil. The other sectors consistently emitted about 40,000 tonnes of NOx per year and it became the 2nd highest NOx emission source after 1994. The other sectors are consisting of domestic energy usage and agriculture. Kim I.S. et al. (2013) and UNEP (2012) showed that the dominant
3.4. Regional distributions of NOx emissions The regional distribution of NOx emissions of REAS 1.1 in 0.5 0.5 grid was shown in Fig. 7. In North Korea, NOx emissions were relatively high in the 1980s in Pyongyang area which is the
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Fig. 6. Sectoral NOx emission trends of North Korea.
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Fig. 7. Regional distribution of NOx emissions of REAS (unit: t yr
capital of North Korea. However, as the NOx emission was decreasing from 1989 to 1997, it is hard to find out any distinct spatial variation of gridded emissions after 1990. The regional distribution of top-down estimated NOx after 1996 was also shown in Fig. 8. As the case of REAS1.1 inventory shown in
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Fig. 7, it is hard to see the regional variation of NOx emissions in North Korea. In Fig. 8, higher emissions in southern Pyongyang area could be barely identified which might be the effect of transport from South Korea rather than the NOx emission in North Korea itself.
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Fig. 8. Regional distribution of NOx emissions of top-down estimated NOx emission (unit: t yr
3.5. Monthly NOx emissions The monthly variations of top-down NOx emissions of both North and South Korea are shown in Fig. 9. Since no monthly
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variation is considered in REAS 1.1, only that of CAPSS in South Korea is shown for comparison. To calculate the monthly value of CAPSS in South Korea, the monthly variation factors of the NOx emissions by Han et al. (2009) were used.
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Usually, NOx emissions are higher in cold season, and they become lower in warm season since more fuels are used in winter than summer in Northeast Asia. However, the monthly NOx emissions in North Korea were high in warm season and low in cold season. This is one of the interesting characteristic of NOx emissions in North Korea. As discussed in section 3.3, the transportation sector is the biggest source of NOx emissions in the developed countries. However, in North Korea, the NOx emissions from other sectors, mainly consisted of domestic and agriculture, were higher than that of transportation sector. Since most of agricultural work is carried out in the warm season, it might be one of the reasons for rather high NOx emissions in North Korea in warm season. Still, further studies are warranted to elucidate this phenomenon. 4. Summary In this study, top-down NOx emissions estimated from satellite observations of NO2 vertical column densities over North Korea from 1996 to 2009 were analyzed. Also, REAS 1.1 from 1980 to 2005 was analyzed with several statistics to find out the trend of NOx emission in North Korea. The top-down estimated NOx emissions were well matched to REAS 1.1 except 2003 and 2005. The other bottom-up inventories were very different from the top-down estimated NOx emissions. Therefore, REAS 1.1 seems to be the most reliable bottom-up NOx emission inventories for North Korea. Thus, further analysis is carried out on the REAS 1.1 data. The NOx emissions from industry sector decreased consequently. The NOx emissions from transportation sector were the 2nd highest in the 1980s, but it also kept decreasing, and the NOx emissions from other sectors (mainly domestic and agriculture) became higher than transportation sector. These trends were not shown in South Korea and it is unusual in other developed countries. It seems to be the unique characteristics of NOx emission in North Korea, resulted from poor energy supply conditions in North Korea. NOx emissions in North Korea were concentrated in Pyongyang area in the 1980s which is the capital of North Korea. However, after the NOx emissions decreased since 1990, it became hard to find out the spatial distribution. The monthly NOx emissions in North Korea were high in warm season and low in cold season, and it seems to be another unique characteristic of NOx emissions in North Korea, because usually, NOx emissions are higher in cold season, and lower in warm season in most developed countries. This is the first study to introduce the NOx emissions in North Korea comparing bottom-up and top-down emission inventories with various statistical data. Though, limited data has been used for analysis because of closed characteristics of North Korea to the world, still it will be a very useful study to understand the NOx emissions in North Korea. Acknowledgments A part of this study was carried out while one of the authors (N.K. Kim) was in NIES by the Global Internship Program from National Research Foundation (NRF) of Korea. This work was also supported by the NRF grant funded by the Korea government (MEST) (2011-0016297 and 2009-0083527) and the Global Environment Research Fund (S-7) by the Ministry of the Environment, Japan. We would like to acknowledge Profs. A. Richter and J. P. Burrows of University of Bremen for providing satellite observation data of GOME and SCIAMACHY. References Bank of Korea, 2012. Economic Statistics Yearbook (in Korean), Seoul, Korea. Byun, D.W., Schere, K.L., 2006. Review of the governing equations, computational algorithms, and other components of the Models-3 Community Multiscale Air Quality (CMAQ) modeling system. Appl. Mech. Rev. 59, 51e77.
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, J.-L., Emmous, L.K., Richter, A., Cammas, J.-P., Edwards, D.P., Lamarque, J.-F., Attie Gille, J.C., Francis, G.L., Deeter, M.N., Warner, J., Ziskin, D.C., Lyjak, L.V., Drummond, J.R., Burrows, J.P., 2003. Tropospheric ozone over the tropical Atlantic: a satellite perspective. J. Geophys. Res. 108 (D8), 4237. Guenther, A., Hewitt, C.N., Erickson, D., Fall, R., Geron, C., Graedel, T., Harley, P., Klinger, L., Lerdau, M., McKay, W.A., Pierce, T., Scholes, B., Steinbrecher, R., Tallamraju, R., Taylor, J., Zimmerman, P., 1995. A global model of natural volatile organic compound emissions. J. Geophys. Res. 100 (D5), 8873e8892. Han, K.M., Song, C.H., Ahn, H.J., Park, R.S., Woo, J.H., Lee, C.K., Richter, A., Burrows, J.P., Kim, J.Y., Hong, J.H., 2009. Investigation of NOx emissions and NOxrelated chemistry in East Asia using CMAQ-predicted and GOME-derived NO2 columns. Atmos. Chem. Phys. 9, 1017e1036. Hayes, P., Hippel, D.V., Bruce, S., 2011. The DPRK energy sector: current status and future engagement options. Korean J. Def. Anal. 23 (2), 159e173. He, Y., Uno, I., Wang, Z., Ohara, T., Sugimoto, N., Shimizu, A., Richter, A., Burrows, J.P., 2007. Variations of the increasing trend of tropospheric NO2 over central east China during the past decade. Atmos. Environ. 41, 4865e4876. Jung, H.S., Kang, K.K., Kang, C.K., 1996. Environmental Issues in North Korea and Direction of Environmental Policy of United Korea (in Korean). Korea Environment Institute, Seoul, Korea. Kim, I.S., Lee, J.Y., Kim, Y.P., 2011. Energy usage and emissions of air pollutants in North Korea. J. Korean Soc. Atmos. Environ. 27 (3), 303e312 (in Korean). Kim, I.S., Lee, J.Y., Kim, Y.P., 2013. Impact of polycyclic aromatic hydrocarbon (PAH) emissions from North Korea to the air quality in the Seoul Metropolitan Area, South Korea. Atmos. Environ. 70, 159e165. Kim, K.S., 2005. A Study of Energy Supply Modeling in North Korea (II) (in Korean). Korea Energy Economics Institute, Uiwang, Korea. Kim, N.K., Kim, Y.P., Morino, Y., Kurokawa, J., Ohara, T., 2013. Verification of NOx emission inventory over South Korea using sectoral activity data and satellite observation of NO2 vertical column densities. Atmos. Environ. 77, 496e508. Kwak, S.J., Cho, S.K., 1999. Estimation of air pollutants' emissions in North Korea: using OLS and vector autoregressive model (in Korean). Korean Econ. Assoc. 47 (4), 153e173. Korean Statistical Information Service (KOSIS), http://kosis.kr, 2011. 11. Kurokawa, J., Yumimoto, K., Uno, I., Ohara, T., 2009a. Adjoint inverse modeling of NOx emissions over eastern China using satellite observations of NO2 vertical column densities. Atmos. Environ. 43, 1878e1887. Kurokawa, J., Ohara, T., Uno, I., Hayasaki, M., Tanimoto, H., 2009b. Influence of meteorological variability on interannual variations of springtime boundary layer ozone over Japan during 1981e2005. Atmos. Chem. Phys. 9, 6287e6304. Martin, R.V., Chance, K., Jacob, D.J., Kurosu, T.P., Spurr, R.J.D., Bucsela, E., Gleason, J.F., Palmer, P.I., Bey, I., Fiore, A.M., Li, Q., Yantosca, R.M., Koelemeijer, R.B.A., 2002. An improved retrieval of tropospheric nitrogen dioxide from GOME. J. Geophys. Res. 107 (D20), 4437. National Institute of Environmental Research (NIER), 2011. National Air Pollutants Emission 2009 (in Korean), Incheon, Korea. Ohara, T., Akimoto, H., Kurokawa, J., Horii, N., Yamaji, K., Yan, X., Hayasaka, T., 2007. An Asian emission inventory of anthropogenic emission sources for the period 1980e2020. Atmos. Chem. Phys. 7, 4419e4444. Pielke, R.A., Cotton, W.R., Walko, R.L., Tremback, C.J., Lyons, W.A., Grasso, L.D., Nicholls, M.E., Moran, M.D., Wesley, D.A., Lee, T.J., Copeland, J.H., 1992. A comprehensive meteorological modeling system e RAMS. Meteorol. Atmos. Phys. 49, 69e91. Richter, A., Burrows, J.P., 2002. Tropospheric NO2 from GOME measurements. Adv. Space Res. 29 (11), 1673e1683. Richter, A., Burrows, J.P., Nüß, H., Granier, C., Niemeier, U., 2005. Increase in tropospheric nitrogen dioxide over China observed from space. Nature 437, 129e132. Streets, D.G., Bond, T.C., Carmichael, G.R., Fernandes, S.D., Fu, Q., He, D., Klimont, Z., Nelson, S.M., Tsai, N.Y., Wang, M.Q., Woo, J.-H., Yarber, K.F., 2003. An inventory of gaseous and primary aerosol emission in Asia in the year 2000. J. Geophys. Res. 108 (D21), 8809,. http://dx.doi.org/10.1029/2002JD003093. United Nations Environment Programme (UNEP), 2003. DPR KOREA: State of the Environment 2003, Pathumthani, Thailand. United Nations Environment Programme (UNEP), 2012. DPR KOREA: Environment and Climate Change Outlook, Pyongyang, North Korea. Uno, I., He, Y., Ohara, T., Yamaji, K., Kurokawa, J.-I., Katayama, M., Wang, Z., Noguchi, K., Hayashida, S., Richter, A., Burrows, J.P., 2007. Systematic analysis of interannual and seasonal variations of model-simulated tropospheric NO2 in Asia and comparison with GOME-satellite data. Atmos. Chem. Phys. 7, 1671e1681. van der A, R.J., Peters, D.H.M.U., Eskes, H., Boersma, K.F., Van Roozendael, M., De Smedt, I., Kelder, H.M., 2006. Detection of the trend and seasonal variation in tropospheric NO2 over China. J. Geophys. Res. 111, D12317. http://dx.doi.org/ 10.1029/2005JD006594. Wang, Y., McElroy, M.B., Martic, R. loV., Streets, D.G., Zhang, Q., Fu, T.M., 2007. Seasonal variability of NOx emissions over east China constrained by satellite observations: Implications for combustion and microbial sources. J. Geophys. Res. 112, D06301. http://dx.doi.org/10.1029/2006JD007538. Yan, X., Akimoto, H., Ohara, T., 2003a. Estimation of nitrous oxide, nitric oxide and ammonia emissions from croplands in East, Southeast and South Asia. Glob. Change Biol. 9, 1080e1096. Yan, X., Shimizu, K., Akimoto, H., Ohara, T., 2003b. Determining fertilizer-induced NO emission ratio from soils by a statistical distribution model. Biol. Fertil. Soils 39, 45e50.
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Yan, X., Ohara, T., Akimoto, H., 2005. Statistical modeling of global soil NOx emissions. Glob. Biogeochem. Cycles 19, GB3019. http://dx.doi.org/10.1029/ 2004GB002276. Zhang, Q., Streets, D.G., He, K., Wang, Y., Richter, A., Burrows, J.P., Uno, I., Jang, C.J., Chen, D., Yao, Z., Lei, Y., 2007. NOx emission trends for China, 1995e2004: the
view from the ground and the view from space. J. Geophys. Res. 112, D22306. http://dx.doi.org/10.1029/2007JD008684. Zhang, Q., Streets, D.G., Carmichael, G.R., He, K.B., Huo, H., Kannari, A., Kilmont, Z., Park, I.S., Reddy, S., 2009. Asian emissions in 2006 for the NASA INTEX-B mission. Atmos. Chem. Phys. 9, 5131e5153.
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Environmental Pollution journal homepage: www.elsevier.com/locate/envpol
Verification of NOx emission inventories over North Korea Na Kyung Kim a, Yong Pyo Kim a, *, Yu Morino b, Jun-ichi Kurokawa c, Toshimasa Ohara b, * a
Department of Environmental Science and Engineering, Ewha Womans University, Seoul, Republic of Korea National Institute for Environmental Studies, Tsukuba, Ibaraki, Japan c Atmospheric Research Department, Asia Center for Air Pollution Research, Niigata, Japan b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 13 March 2014 Received in revised form 24 June 2014 Accepted 28 June 2014 Available online 26 July 2014
In this study, the top-down NOx emissions estimated from satellite observations of NO2 vertical column densities over North Korea from 1996 to 2009 were analyzed. Also, a bottom-up NOx emission inventory from REAS 1.1 from 1980 to 2005 was analyzed with several statistics. REAS 1.1 was in good agreement with the top-down approach for both trend and amount. The characteristics of NOx emissions in North Korea were quite different from other developed countries including South Korea. In North Korea, emissions from industry sector was the highest followed by transportation sector in the 1980s. However, after 1990, the NOx emissions from other sector, mainly agriculture, became the 2nd highest. Also, no emission centers such as urban areas or industrial areas were distinctively observed. Finally, the monthly NOx emissions were high during the warm season. © 2014 Elsevier Ltd. All rights reserved.
Keywords: North Korea NOx emission inventories REAS 1.1 Top down NOx estimation
1. Introduction NOx is a major air pollutant in Northeast Asia including China, South and North Korea and Japan, and the emission of NOx in the region is drastically increasing (see, for example, Zhang et al., 2009). NOx is emitted from anthropogenic sources such as fossil fuel combustion and biomass burning, as well as natural sources such as lightning and microbiological processes in soil and plays important roles in oxidation processes in the atmosphere. Several studies on NOx emissions have been carried out to find out their influence on the air quality in Northeast Asia (Uno et al., 2007; Wang et al., 2007; Zhang et al., 2007). Recently, several studies using satellite measurements reported that NO2 vertical column density have increased significantly in East Asia (Richter et al., 2005; He et al., 2007). North Korea is also located in Northeast Asia (Fig. 1), but the studies about the emissions of air pollutants or air quality in North Korea are rare due to its closed characteristics to the outside world. In general, emission inventories are made by the bottom-up approach, which is based on the combinations of activity statistics (such as energy consumption and industrial production) and source-or region-specific emission factors (Ohara et al., 2007; Kurokawa et al., 2009a). However, North Korea publishes few statistics on its energy sector or other economic activities (UNEP, 2003, 2012), and few quantitative estimates describing activities in the
* Corresponding authors. E-mail addresses: [email protected] (Y.P. Kim), [email protected] (T. Ohara). http://dx.doi.org/10.1016/j.envpol.2014.06.034 0269-7491/© 2014 Elsevier Ltd. All rights reserved.
North Korean energy sector made by outside groups tend to be uneven in quality (Hayes et al., 2011). Consequently, the emission inventories of North Korea are very rare and and contain large uncertainty. Kim et al. (2011) reviewed the characteristics of energy consumption, emissions of air pollutants, and ambient air quality in North Korea. Kim I.S. et al. (2013) identified the characteristics of energy consumption in North Korea as (1) very low energy consumption per capita, (2) high dependence on coal and biofuel, and (3) low level of combustion and control technologies. Further, they combined the Chemical Mass balance Model (CMB) result for the particulate Polycyclic Aromatic Hydrocarbons (PAHs) data in Seoul and backward trajectory analysis result and estimated that at least 20% of the particulate PAHs observed in winter in Seoul were from North Korea (Kim I.S. et al., 2013). However, without reliable emission inventory data for North Korea, it is hard to validate these study results. In this case, “top-down” or inverse modeling approaches, in which emissions are optimized in order to reduce the differences between the simulated and observed data, is a powerful method that alleviates the problems of the bottom-up approach and estimate the emissions of air pollutants (Kurokawa et al., 2009a). For example, Kim N.K. et al. (2013) compared two bottom-up emission inventories, Clean Air Policy Support System (CAPSS) and Regional Emission inventory for ASia (REAS 1.1) and one top-down emission estimated from satellite observation on South Korea. They have shown that the top-down emission result is close to the CAPSS emission result. They also found that REAS 1.1 and the top-down emission showed the same
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Fig. 1. The map of North and South Korea.
trend while the absolute amounts were different by about 25%. They further identified that the difference was mainly caused by spatial distribution of emissions from transportation sector. They concluded that the top-down approach is a reliable one. To understand the characteristics of the emissions of NOx in North Korea, top-down NOx emissions estimated from satellite observations of NO2 vertical column densities over North Korea from 1996 to 2009 were analyzed, and compared with the REAS 1.1 emission inventory which includes the air pollutant emissions in North Korea from 1980 to 2005. Also these were compared with several statistics to find out the trend and characteristics. These results are compared with those in South Korea to clarify the characteristics of NOx emissions in North Korea. It is the first study to compare the bottom-up and the top-down emission inventories with various statistical data for North Korea, and therefore, it will be useful to understand the NOx emission in North Korea. 2. Data 2.1. Bottom-up emission inventory The bottom-up emission inventory analyzed in this study is Regional Emission inventory in ASia (REAS 1.1) developed by Ohara et al. (2007), which includes the air pollutant emission from North Korea. REAS 1.1 includes ten air pollutants, NOx, SO2, CO, Black Carbon (BC), Organic Carbon (OC), CO2, N2O, NH3, CH4, and Non-
Methane Volatile Organic Compounds (NMVOCs) from anthropogenic activities. The target domain of REAS 1.1 covers 24 countries in East, Southeast, and South Asia. Emissions were estimated on the basis of activity data at district levels for China (30 provinces), India (20 states), Japan (6 sub-regions), South Korea (4 sub-regions), and Pakistan (5 sub-regions). For other countries including North Korea, national emissions were estimated on the basis of activity data at the national level (Ohara et al., 2007). Emissions were estimated as a product of the activity data, emission factors, and removal efficiency of emission controls. Region-specific emission factors for subdivided source sectors were developed from a wide range of literature and were used to estimate emissions on district and country levels. These emissions, estimated on district and country levels, were divided into a 0.5 0.5 grid by using index databases, i.e. population data, information on the positions of large point sources (LPSs), land cover data sets, and land area data sets. Details on REAS 1.1 could be found in Ohara et al. (2007). In this study, the NOx emission inventory of REAS 1.1 from 1980 to 2003 (Ohara et al., 2007; http://www.jamstec.go.jp/frsgc/ research/d4/emission.htm) and extended data till 2005 (Kurokawa et al., 2009b) were analyzed. 2.2. Top-down NOx emission inventory Detailed description on the top-down NOx emission inventory was given in Kim N.K. et al. (2013). Briefly, a simple iteration
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grid cells is not fully reflected. So, in this study, relatively coarse horizontal resolution (80 km) is used in CMAQ. Note that in this methodology, NOx emissions were strongly forced to be adjusted by the differences of observed and simulated NO2 VCDs in each grid. So, influence of initial NOx emissions is expected to be small. Monthly averaged top-down NOx emissions in North Korea were estimated using this methodology from January 1996 to December 2009. 3. Results 3.1. Long term trend of the NOx emissions In Fig. 2, the total amounts of NOx emissions of North Korea from REAS 1.1 between 1980 and 2005 are shown, and compared to the total amounts of NOx emissions of South Korea from REAS 1.1 and CAPSS developed by National Institute of Environmental Research (NIER), South Korea (NIER, 2011). In the early 1980s, the total amounts of NOx emissions of North Korea were comparable to those of South Korea, however, the emissions decreased below 10e20% of South Korea after the 1990s due to poor economic conditions in North Korea (Kim et al., 2011; Kim I.S. et al., 2013). Kim I.S. et al. (2013) found that with the collapse of the former Soviet Union in 1989, the energy supply of North Korea, especially that of petroleum, has decreased drastically, reducing emissions of air pollutants. To figure out detailed economic conditions in North Korea, several statistics were investigated and shown in Fig. 3. The economic growth rates of North Korea were negative, about 5% from 1990 till 1997, and the Gross National Income (GNI) and total primary energy consumption kept decreasing until 1998 (Bank of Korea (2012)). After 1999, the economic growth rate became positive, but the economic situation in North Korea was still in poor condition, and the total energy consumption in North Korea kept low, below 2 million tonne of oil equivalent (TOE) per year. In Fig. 4, the energy structures of total primary energy consumption for North Korea between 1965 and 2009 were shown (Korean Statistical Information Service, 2011). During the whole period, coal was the main energy source in North Korea, and the proportions of coal use were more than 60%. However, the absolute amount of coal mining and, thus, consumption was decreased in the 1990s, and then did not change much because of antiquated mining instruments and the deepening of the coal mines. Furthermore, oil imports have not been affordable in current
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methodology was used to obtain monthly top-down NOx emissions with which chemical transport model (CTM) reproduces the satellite observation of monthly NO2 vertical column densities (VCDs). In this study, the three-dimensional regional-scale chemical transport modeling system developed jointly by Kyushu University and the National Institute for Environmental Studies (NIES) (Uno et al., 2007) was used. The Models-3 Community Multiscale Air Quality (CMAQ) modeling system (Byun and Schere, 2006) and the Regional Atmospheric Modeling System (RAMS) version 4.4 (Pielke et al., 1992) were adopted for the system. The horizontal model domain for the CMAQ simulation was 6240 km 5440 km on a rotated polar stereographic map projection centered at 25 N, 115 E, with a grid resolution of 80 km 80 km. For vertical resolution, the modeling system employed 14 grid points extending from the surface to 22 km with 14 stretching grid layers in the sigma-z coordinate system. The CMAQ full chemistry model requires the emission inventories not only for NOx but also other chemical species for input data. Anthropogenic emissions of all species were taken from REAS 1.1 (Ohara et al., 2007; See Section 2.1 for detail). For NOx emissions from soil sources, datasets were prepared based on monthly estimations for the year 2001 and annual emissions for the year 1990 by Yan et al. (2003a, b, 2005). Data for 2001 were adopted for the years after 2002. For the years before 2001, first, monthly emissions for 1990 were estimated assuming the same monthly variations as in 2001, and then emissions were linearly interpolated to each year. Biogenic emissions of isoprene and monoterpenes were taken from monthly estimations for the 1990s by Guenther et al. (1995), and emissions of all species from vegetation fires were taken from inventories for the late 1990's from Streets et al. (2003) and used for all the years. In this study, lightning NOx emission was not included because lightning NOx was considered to contribute little to NOx VCDs during daytime (Martin et al., 2002; Edwards et al., 2003). For satellite-derived NO2 VCDs, Global Ozone Monitoring Experiment (GOME) and Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) observation data are used. GOME was a passive remote sensing instrument on board the ERS-2 satellite launched in April 1995. It provided observed data with a resolution of 40 km (latitude) 320 km (longitude) until June 2003. The ERS-2 satellite crosses the equator at 1030 Local Time (LT) in a sun-synchronous polar orbit, and global coverage was archived every 3 days. The version 2 tropospheric NO2 VCDs data products retrieved by the University of Bremen were used in this study. Richter et al. (2005) indicate that a rough estimate of the GOME retrieval errors is an additive error of approximately 0.5e1.0 1015 molecules cm 2 and a relative error of 40e60% for monthly averages over polluted regions. Detailed description for GOME NO2 VCDs retrieval was provided by Richter and Burrows (2002) and Richter et al. (2005). SCHIAMACHY is also a passive remote sensing instrument observing backscattered, reflected, transmitted or emitted radiation from the atmosphere and surface of the Earth. SCHIAMACHY is on board Environmental Satellite (ENVISAT) which was launched in March 2002 and has a dayside equatorial crossing time of 1000 LT. Resolution of SCIAMACHY is 30 km (latitude) 60 km (longitude). SCIAMACHY tropospheric excess NO2 VCDs version 0.7 and 0.8 retrieved by the University of Bremen were used in this study. Richter et al. (2005) and van der A et al. (2006) have shown that the bias between GOME and SCHIAMACHY is smaller than the minimum error (0.5 1015 molecules cm 2) in the data, and therefore, the bias can be neglected. In this study, the retrievals of GOME from 1996 to 2002 and those of SCIAMACHY from 2003 to 2009 were used. In this methodology, the influence of NOx emissions on NO2 VCDs is adjusted only by the column just over the emission grid. It means that the influence of transport of NOx from the neighboring
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Fig. 2. NOx emission trends of North Korea from REAS and South Korea from CAPSS and REAS.
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economic condition in North Korea. Therefore, the NOx emission in North Korea is projected to keep low for a while. 3.2. Comparison to other bottom- up and top-down estimated NOx emissions In Fig. 5, the NOx emissions in North Korea from REAS 1.1 and other bottom-up emission inventories are shown, and they are compared with the top-down estimated NOx emissions. Since uncertainties of the top-down estimated NOx emissions tend to be larger in wintertime due to relatively long lifetime of NOx, the top-down estimated NOx emission with and without winter were shown, respectively. The top-down estimated NOx emissions with winter includes the whole estimated result with the uncertainties in winter time. On the other hand, the top-down estimated NOx emissions without winter were calculated by applying factor of 1.5 to the top-down estimated NOx emissions only 8 months from March to October to exclude the uncertainties in wintertime.
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First of all, the top-down estimated NOx emissions were well matched to REAS 1.1 except for 2003 and 2005. Especially, the absolute values of top-down estimated NOx emission between 1996 and 2002 were quite close to REAS 1.1. Other bottom-up inventories were highly different from the top-down estimated NOx emissions. The NOx emission inventory from Jung et al. (1996) (see the right y-axis) was more than 10 times higher than the top-down estimated NOx emissions in 1994. The NOx emission inventory from Kwak and Cho (1999) was about 2 times higher than the top-down estimated NOx emissions in 2003. On the other hand, NOx emission inventories from Kim (2005) were much smaller than the top-down estimated NOx emissions. To sum it up, the top-down emission inventory matches better with REAS 1.1 than other available emission inventories, and therefore, REAS 1.1 seems to be the most reliable bottom-up NOx emission inventories for North Korea. The trend of the top-down result for the whole year and the top-down results without winter (March to October only) matched well, and the top-down estimated NOx without winter was higher than the top-down estimated NOx for the whole year. It is different from the trend shown for South Korea (Kim et al., 2013). It may suggest higher NOx emission in summer than winter in North Korea and it will be discussed in section 3.5. 3.3. Sectoral NOx emission trends Since REAS 1.1 emission inventory is in good agreement with the top-down approach result for both trend and absolute amount, further analysis is carried out on the REAS 1.1 data. In Fig. 6, sectoral NOx emission trends of North Korea between 1980 and 2005 from REAS 1.1 are shown. During the whole period, industry was the biggest source of NOx emission in North Korea, about a half of the total. However, its emission amount decreased almost half from the middle of the 1980s to the late 1990s. The main energy source of industry in North Korea has been coal which has been produced by the mining in North Korea, and as it was mentioned in section 3.1, the absolute amounts of coal mining kept decreasing. Therefore, the NOx emission from industry sector decreased consequently. The NOx emission from transportation sector was the 2nd highest in the 1980s (22% on the average), but it also kept decreasing. Since the mid-1990s, the NOx emissions from transformation and other sectors (mainly consisted by domestic and agriculture) became higher than transportation sector and, recently, it took 18% on the average.
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Fig. 5. Comparisons of the bottom-up and the top-down NOx emission data in North Korea. The right y-axis scale is used for the emission data of Jung et al. (1996).
domestic energy types in North Korea have been coal and biofuel. In North Korea, overall energy supply has been in poor condition, and therefore only NOx emissions from domestic energy use and agriculture barely keep certain values, and this trend affects the total NOx emissions in North Korea.
Contrastingly, in South Korea, the transportation sector has been the biggest source of NOx emissions, and its contribution to the total NOx emission is increasing (Kim N.K. et al., 2013). This trend is common not only in South Korea but also in other developed countries. Therefore, this trend is the characteristic of NOx emission in North Korea, and it is also explained by poor energy supply conditions in North Korea, especially, oil. The other sectors consistently emitted about 40,000 tonnes of NOx per year and it became the 2nd highest NOx emission source after 1994. The other sectors are consisting of domestic energy usage and agriculture. Kim I.S. et al. (2013) and UNEP (2012) showed that the dominant
3.4. Regional distributions of NOx emissions The regional distribution of NOx emissions of REAS 1.1 in 0.5 0.5 grid was shown in Fig. 7. In North Korea, NOx emissions were relatively high in the 1980s in Pyongyang area which is the
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Fig. 7. Regional distribution of NOx emissions of REAS (unit: t yr
capital of North Korea. However, as the NOx emission was decreasing from 1989 to 1997, it is hard to find out any distinct spatial variation of gridded emissions after 1990. The regional distribution of top-down estimated NOx after 1996 was also shown in Fig. 8. As the case of REAS1.1 inventory shown in
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Fig. 7, it is hard to see the regional variation of NOx emissions in North Korea. In Fig. 8, higher emissions in southern Pyongyang area could be barely identified which might be the effect of transport from South Korea rather than the NOx emission in North Korea itself.
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Fig. 8. Regional distribution of NOx emissions of top-down estimated NOx emission (unit: t yr
3.5. Monthly NOx emissions The monthly variations of top-down NOx emissions of both North and South Korea are shown in Fig. 9. Since no monthly
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variation is considered in REAS 1.1, only that of CAPSS in South Korea is shown for comparison. To calculate the monthly value of CAPSS in South Korea, the monthly variation factors of the NOx emissions by Han et al. (2009) were used.
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Usually, NOx emissions are higher in cold season, and they become lower in warm season since more fuels are used in winter than summer in Northeast Asia. However, the monthly NOx emissions in North Korea were high in warm season and low in cold season. This is one of the interesting characteristic of NOx emissions in North Korea. As discussed in section 3.3, the transportation sector is the biggest source of NOx emissions in the developed countries. However, in North Korea, the NOx emissions from other sectors, mainly consisted of domestic and agriculture, were higher than that of transportation sector. Since most of agricultural work is carried out in the warm season, it might be one of the reasons for rather high NOx emissions in North Korea in warm season. Still, further studies are warranted to elucidate this phenomenon. 4. Summary In this study, top-down NOx emissions estimated from satellite observations of NO2 vertical column densities over North Korea from 1996 to 2009 were analyzed. Also, REAS 1.1 from 1980 to 2005 was analyzed with several statistics to find out the trend of NOx emission in North Korea. The top-down estimated NOx emissions were well matched to REAS 1.1 except 2003 and 2005. The other bottom-up inventories were very different from the top-down estimated NOx emissions. Therefore, REAS 1.1 seems to be the most reliable bottom-up NOx emission inventories for North Korea. Thus, further analysis is carried out on the REAS 1.1 data. The NOx emissions from industry sector decreased consequently. The NOx emissions from transportation sector were the 2nd highest in the 1980s, but it also kept decreasing, and the NOx emissions from other sectors (mainly domestic and agriculture) became higher than transportation sector. These trends were not shown in South Korea and it is unusual in other developed countries. It seems to be the unique characteristics of NOx emission in North Korea, resulted from poor energy supply conditions in North Korea. NOx emissions in North Korea were concentrated in Pyongyang area in the 1980s which is the capital of North Korea. However, after the NOx emissions decreased since 1990, it became hard to find out the spatial distribution. The monthly NOx emissions in North Korea were high in warm season and low in cold season, and it seems to be another unique characteristic of NOx emissions in North Korea, because usually, NOx emissions are higher in cold season, and lower in warm season in most developed countries. This is the first study to introduce the NOx emissions in North Korea comparing bottom-up and top-down emission inventories with various statistical data. Though, limited data has been used for analysis because of closed characteristics of North Korea to the world, still it will be a very useful study to understand the NOx emissions in North Korea. Acknowledgments A part of this study was carried out while one of the authors (N.K. Kim) was in NIES by the Global Internship Program from National Research Foundation (NRF) of Korea. This work was also supported by the NRF grant funded by the Korea government (MEST) (2011-0016297 and 2009-0083527) and the Global Environment Research Fund (S-7) by the Ministry of the Environment, Japan. We would like to acknowledge Profs. A. Richter and J. P. Burrows of University of Bremen for providing satellite observation data of GOME and SCIAMACHY. References Bank of Korea, 2012. Economic Statistics Yearbook (in Korean), Seoul, Korea. Byun, D.W., Schere, K.L., 2006. Review of the governing equations, computational algorithms, and other components of the Models-3 Community Multiscale Air Quality (CMAQ) modeling system. Appl. Mech. Rev. 59, 51e77.
243
, J.-L., Emmous, L.K., Richter, A., Cammas, J.-P., Edwards, D.P., Lamarque, J.-F., Attie Gille, J.C., Francis, G.L., Deeter, M.N., Warner, J., Ziskin, D.C., Lyjak, L.V., Drummond, J.R., Burrows, J.P., 2003. Tropospheric ozone over the tropical Atlantic: a satellite perspective. J. Geophys. Res. 108 (D8), 4237. Guenther, A., Hewitt, C.N., Erickson, D., Fall, R., Geron, C., Graedel, T., Harley, P., Klinger, L., Lerdau, M., McKay, W.A., Pierce, T., Scholes, B., Steinbrecher, R., Tallamraju, R., Taylor, J., Zimmerman, P., 1995. A global model of natural volatile organic compound emissions. J. Geophys. Res. 100 (D5), 8873e8892. Han, K.M., Song, C.H., Ahn, H.J., Park, R.S., Woo, J.H., Lee, C.K., Richter, A., Burrows, J.P., Kim, J.Y., Hong, J.H., 2009. Investigation of NOx emissions and NOxrelated chemistry in East Asia using CMAQ-predicted and GOME-derived NO2 columns. Atmos. Chem. Phys. 9, 1017e1036. Hayes, P., Hippel, D.V., Bruce, S., 2011. The DPRK energy sector: current status and future engagement options. Korean J. Def. Anal. 23 (2), 159e173. He, Y., Uno, I., Wang, Z., Ohara, T., Sugimoto, N., Shimizu, A., Richter, A., Burrows, J.P., 2007. Variations of the increasing trend of tropospheric NO2 over central east China during the past decade. Atmos. Environ. 41, 4865e4876. Jung, H.S., Kang, K.K., Kang, C.K., 1996. Environmental Issues in North Korea and Direction of Environmental Policy of United Korea (in Korean). Korea Environment Institute, Seoul, Korea. Kim, I.S., Lee, J.Y., Kim, Y.P., 2011. Energy usage and emissions of air pollutants in North Korea. J. Korean Soc. Atmos. Environ. 27 (3), 303e312 (in Korean). Kim, I.S., Lee, J.Y., Kim, Y.P., 2013. Impact of polycyclic aromatic hydrocarbon (PAH) emissions from North Korea to the air quality in the Seoul Metropolitan Area, South Korea. Atmos. Environ. 70, 159e165. Kim, K.S., 2005. A Study of Energy Supply Modeling in North Korea (II) (in Korean). Korea Energy Economics Institute, Uiwang, Korea. Kim, N.K., Kim, Y.P., Morino, Y., Kurokawa, J., Ohara, T., 2013. Verification of NOx emission inventory over South Korea using sectoral activity data and satellite observation of NO2 vertical column densities. Atmos. Environ. 77, 496e508. Kwak, S.J., Cho, S.K., 1999. Estimation of air pollutants' emissions in North Korea: using OLS and vector autoregressive model (in Korean). Korean Econ. Assoc. 47 (4), 153e173. Korean Statistical Information Service (KOSIS), http://kosis.kr, 2011. 11. Kurokawa, J., Yumimoto, K., Uno, I., Ohara, T., 2009a. Adjoint inverse modeling of NOx emissions over eastern China using satellite observations of NO2 vertical column densities. Atmos. Environ. 43, 1878e1887. Kurokawa, J., Ohara, T., Uno, I., Hayasaki, M., Tanimoto, H., 2009b. Influence of meteorological variability on interannual variations of springtime boundary layer ozone over Japan during 1981e2005. Atmos. Chem. Phys. 9, 6287e6304. Martin, R.V., Chance, K., Jacob, D.J., Kurosu, T.P., Spurr, R.J.D., Bucsela, E., Gleason, J.F., Palmer, P.I., Bey, I., Fiore, A.M., Li, Q., Yantosca, R.M., Koelemeijer, R.B.A., 2002. An improved retrieval of tropospheric nitrogen dioxide from GOME. J. Geophys. Res. 107 (D20), 4437. National Institute of Environmental Research (NIER), 2011. National Air Pollutants Emission 2009 (in Korean), Incheon, Korea. Ohara, T., Akimoto, H., Kurokawa, J., Horii, N., Yamaji, K., Yan, X., Hayasaka, T., 2007. An Asian emission inventory of anthropogenic emission sources for the period 1980e2020. Atmos. Chem. Phys. 7, 4419e4444. Pielke, R.A., Cotton, W.R., Walko, R.L., Tremback, C.J., Lyons, W.A., Grasso, L.D., Nicholls, M.E., Moran, M.D., Wesley, D.A., Lee, T.J., Copeland, J.H., 1992. A comprehensive meteorological modeling system e RAMS. Meteorol. Atmos. Phys. 49, 69e91. Richter, A., Burrows, J.P., 2002. Tropospheric NO2 from GOME measurements. Adv. Space Res. 29 (11), 1673e1683. Richter, A., Burrows, J.P., Nüß, H., Granier, C., Niemeier, U., 2005. Increase in tropospheric nitrogen dioxide over China observed from space. Nature 437, 129e132. Streets, D.G., Bond, T.C., Carmichael, G.R., Fernandes, S.D., Fu, Q., He, D., Klimont, Z., Nelson, S.M., Tsai, N.Y., Wang, M.Q., Woo, J.-H., Yarber, K.F., 2003. An inventory of gaseous and primary aerosol emission in Asia in the year 2000. J. Geophys. Res. 108 (D21), 8809,. http://dx.doi.org/10.1029/2002JD003093. United Nations Environment Programme (UNEP), 2003. DPR KOREA: State of the Environment 2003, Pathumthani, Thailand. United Nations Environment Programme (UNEP), 2012. DPR KOREA: Environment and Climate Change Outlook, Pyongyang, North Korea. Uno, I., He, Y., Ohara, T., Yamaji, K., Kurokawa, J.-I., Katayama, M., Wang, Z., Noguchi, K., Hayashida, S., Richter, A., Burrows, J.P., 2007. Systematic analysis of interannual and seasonal variations of model-simulated tropospheric NO2 in Asia and comparison with GOME-satellite data. Atmos. Chem. Phys. 7, 1671e1681. van der A, R.J., Peters, D.H.M.U., Eskes, H., Boersma, K.F., Van Roozendael, M., De Smedt, I., Kelder, H.M., 2006. Detection of the trend and seasonal variation in tropospheric NO2 over China. J. Geophys. Res. 111, D12317. http://dx.doi.org/ 10.1029/2005JD006594. Wang, Y., McElroy, M.B., Martic, R. loV., Streets, D.G., Zhang, Q., Fu, T.M., 2007. Seasonal variability of NOx emissions over east China constrained by satellite observations: Implications for combustion and microbial sources. J. Geophys. Res. 112, D06301. http://dx.doi.org/10.1029/2006JD007538. Yan, X., Akimoto, H., Ohara, T., 2003a. Estimation of nitrous oxide, nitric oxide and ammonia emissions from croplands in East, Southeast and South Asia. Glob. Change Biol. 9, 1080e1096. Yan, X., Shimizu, K., Akimoto, H., Ohara, T., 2003b. Determining fertilizer-induced NO emission ratio from soils by a statistical distribution model. Biol. Fertil. Soils 39, 45e50.
244
N.K. Kim et al. / Environmental Pollution 195 (2014) 236e244
Yan, X., Ohara, T., Akimoto, H., 2005. Statistical modeling of global soil NOx emissions. Glob. Biogeochem. Cycles 19, GB3019. http://dx.doi.org/10.1029/ 2004GB002276. Zhang, Q., Streets, D.G., He, K., Wang, Y., Richter, A., Burrows, J.P., Uno, I., Jang, C.J., Chen, D., Yao, Z., Lei, Y., 2007. NOx emission trends for China, 1995e2004: the
view from the ground and the view from space. J. Geophys. Res. 112, D22306. http://dx.doi.org/10.1029/2007JD008684. Zhang, Q., Streets, D.G., Carmichael, G.R., He, K.B., Huo, H., Kannari, A., Kilmont, Z., Park, I.S., Reddy, S., 2009. Asian emissions in 2006 for the NASA INTEX-B mission. Atmos. Chem. Phys. 9, 5131e5153.