Systematic analysis of interannual and seasonal variations of model-simulated tropospheric NO<sub>2</sub> in Asia and comparison with GOME-satellite data

Abstract

Abstract. Systematic analyses of interannual and seasonal variations of tropospheric NO 2 vertical column densities (VCDs) based on GOME satellite data and the regional scale chemical transport model (CTM), Community Multi-scale Air Quality (CMAQ), are presented for the atmosphere over eastern Asia between 1996 and June 2003. A newly developed year-by-year emission inventory (REAS) was used in CMAQ. The horizontal distribution of annual averaged GOME NO 2 VCDs generally agrees well with the CMAQ results. However, CMAQ/REAS results underestimate the GOME retrievals with factors of 2-4 over polluted industrial regions such as Central East China (CEC), a major part of Korea, Hong Kong, and central and western Japan. The most probable reasons for the underestimation typically over the CEC are accuracy of the basic energy statistic data, emission factors, and socio-economic data used for construction of emission inventory. For the Japan region, GOME and CMAQ NO 2 data show reasonable agreement with respect to interannual variation and show no clear increasing trend. For CEC, GOME and CMAQ NO 2 data indicate a very rapid increasing trend from 2000. Analyses of the seasonal cycle of NO 2 VCDs show that GOME data have larger dips than CMAQ NO 2 during February-April and September-November. Sensitivity experiments with fixed emission intensity reveal that the detection of emission trends from satellite in fall or winter has a larger error caused by the variability of meteorology. Examination during summer time and annual averaged NO 2 VCDs are robust with respect to variability of meteoCorrespondence to: I. Uno (uno@riam.kyushu-u.ac.jp) rology and are therefore more suitable for analyses of emission trends. Analysis of recent trends of annual emissions in China shows that the increasing trends of 1996-1998 and 2000-2002 for GOME and CMAQ/REAS show good agreement, but the rate of increase by GOME is approximately 10-11% yr −1 after 2000; it is slightly steeper than CMAQ/REAS (8-9% yr −1 ). The greatest difference was apparent between the years 1998 and 2000: CMAQ/REAS only shows a few percentage points of increase, whereas GOME gives a greater than 8% yr −1 increase. The exact reason remains unclear, but the most likely explanation is that the emission trend based on the Chinese emission related statistics underestimates the rapid growth of emissions.

Can a global model reproduce observed trends in summertime surface ozone levels?

“…Indeed, it has been suggested that the REAS emission inventory used in our study for Asia underestimates Asian NO x emissions and trends (Kurokawa et al, 2009;Uno et al, 2007). More precisely, Uno et al …”

Interannual variation in the fine-mode MODIS aerosol optical depth and its relationship to the changes in sulfur dioxide emissions in China between 2000 and 2010

“…4.4) (Byun and Schere, 2006) Uno et al (2007) and Itahashi et al (2010). Therefore, here we only describe aspects relevant to this study.…”

Regional modeling of tropospheric NO<sub>2</sub> vertical column density over East Asia during the period 2000–2010: comparison with multisatellite observations

“…Because of the short lifetime of NO x in the troposphere, satellite NO 2 observations are closely correlated to surface NO x emissions. The tropospheric NO 2 VCD retrieved from satellites has been successfully used to evaluate and quantify the spatial distribution and long-term trends of NO x emissions van der A et al, 2008;Han et al, 2009;Lamsal et al, 2011;Schneider and van der A, 2012).…”

“…In recent years, advances in satellite technology and the development of new instruments and algorithms have allowed for observations of the NO 2 vertical column density (VCD) from space, providing useful information for airquality research (e.g., Richter et al, 2005;van der A et al, 2008;Irie et al, 2009). A global picture of the spatial distribution of the NO 2 VCD is now available because satellite measurements provide global coverage in a very short time (between 1 and 6 days depending on the instrument although more time is needed when cloud cover is present).…”